bayes.bib

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@Article{Kass2006a,
  author       = {Kass, Robert E.},
  title        = {Kinds of {Bayesians} (comment on articles by {Berger} and by {Goldstein})},
  journaltitle = {Bayesian Analysis},
  date         = {2006-09},
  volume       = {1},
  number       = {3},
  pages        = {437--440},
  doi          = {10.1214/06-BA116E},
  fjournal     = {Bayesian Analysis},
  publisher    = {International Society for Bayesian Analysis},
  timestamp    = {2017-05-21},
}

@WWW{Clark2016a,
  author    = {Clark, Michael},
  title     = {{Bayesian} basics},
  date      = {2016-04-26},
  url       = {https://m-clark.github.io/docs/IntroBayes.html},
  timestamp = {2017-05-21},
}

@Book{McElreath2016a,
  author    = {McElreath, Richard},
  title     = {Statistical Rethinking},
  year      = {2016},
  date      = {2016-12-08},
  publisher = {Apple Academic Press Inc.},
  isbn      = {1482253445},
  pagetotal = {487},
  ean       = {9781482253443},
}

@Book{Kruschke2015a,
  author    = {Kruschke, John K.},
  title     = {Doing {Bayesian} Data Analysis},
  year      = {2015},
  date      = {2015-01-11},
  publisher = {Elsevier LTD, Oxford},
  isbn      = {0124058884},
  ean       = {9780124058880},
  timestamp = {2017-05-21},
}

@Book{BDA3,
  author    = {Gelman, Andrew and Carlin, John B. and Stern, Hal S. and Dunson, David B. and Vehtari, Aki},
  title     = {{Bayesian} Data Analysis},
  year      = {2013},
  date      = {2013-11-05},
  publisher = {Taylor \& Francis Ltd},
  isbn      = {1439840954},
  pagetotal = {675},
  ean       = {9781439840955},
  timestamp = {2017-05-14},
}

@Book{EfronHastie2016a,
  author    = {Efron, Bradley and Hastie, Trevor},
  title     = {Computer age statistical inference},
  year      = {2016},
  date      = {2016-07-31},
  publisher = {Cambridge University Pr.},
  isbn      = {1107149894},
  ean       = {9781107149892},
  timestamp = {2017-03-23},
}

@Book{GelmanHill2007a,
  author    = {Gelman, Andrew and Hill, Jennifer},
  title     = {Data Analysis Using Regression and Multilevel / Hierarchical Models},
  year      = {2007},
  date      = {2007-06-11},
  publisher = {Cambridge University Pr.},
  isbn      = {052168689X},
  pagetotal = {648},
  ean       = {9780521686891},
}

@Article{EroshevaCurtis2017a,
  author    = {Elena A. Erosheva and S. McKay Curtis},
  title     = {Dealing with Reflection Invariance in Bayesian Factor Analysis},
  journal   = {Psychometrika},
  year      = {2017},
  month     = mar,
  doi       = {10.1007/s11336-017-9564-y},
  publisher = {Springer Nature},
  timestamp = {2018.05.01},
}

@Book{Murphy2012a,
  author    = {Murphy, Kevin P.},
  title     = {Machine learning},
  year      = {2012},
  date      = {2012-09-18},
  publisher = {MIT Press Ltd},
  isbn      = {0262018020},
  pagetotal = {1104},
  ean       = {9780262018029},
}

@Book{RobertCasella2009a,
  author    = {Robert, Christian P. and Casella, George},
  title     = {Introducing {Monte} {Carlo} Methods with {R}},
  year      = {2009},
  date      = {2009-12-10},
  publisher = {Springer},
  isbn      = {1441915753},
  doi       = {10.1007/978-1-4419-1576-4},
  ean       = {9781441915757},
  timestamp = {2017-05-21},
}

@Book{BlitzsteinHwang2014a,
  author    = {Blitzstein, Joseph K. and Hwang, Jessica},
  title     = {Introduction to probability},
  year      = {2014},
  date      = {2014-08-22},
  publisher = {Taylor \& Francis Inc},
  isbn      = {1466575573},
  pagetotal = {596},
  ean       = {9781466575578},
}

@Book{Jaynes2003a,
  author    = {Jaynes, E. T.},
  title     = {Probability theory},
  date      = {2003},
  publisher = {Cambridge University Pr.},
  isbn      = {0521592712},
  ean       = {9780521592710},
  timestamp = {2017.04.25},
}

@Book{Stone2013a,
  author    = {Stone, James V.},
  title     = {{Bayes’} Rule},
  year      = {2013},
  date      = {2013-06-04},
  publisher = {Tutorial Introductions},
  isbn      = {0956372848},
  pagetotal = {188},
  ean       = {9780956372840},
  timestamp = {2017-05-14},
}

@Book{Davidson-Pilon2015a,
  author    = {Davidson-Pilon, Cameron},
  title     = {{Bayesian} methods for hackers},
  year      = {2015},
  date      = {2015-10-02},
  publisher = {Addison Wesley},
  isbn      = {0133902838},
  pagetotal = {256},
  ean       = {9780133902839},
  timestamp = {2017-05-21},
}

@Book{MacKay2003a,
  author    = {MacKay, David J. C.},
  title     = {Information theory, inference and learning algorithms},
  year      = {2003},
  date      = {2003-09-11},
  publisher = {Cambridge University Pr.},
  isbn      = {0521642981},
  ean       = {9780521642989},
}

@Article{Efron2013a,
  author       = {Efron, B.},
  title        = {{Bayes’} theorem in the 21st century},
  journaltitle = {Science},
  date         = {2013-06},
  volume       = {340},
  number       = {6137},
  pages        = {1177--1178},
  doi          = {10.1126/science.1236536},
  publisher    = {American Association for the Advancement of Science (AAAS)},
  timestamp    = {2017-05-14},
}

@Article{SmaldinoMcElreath2016a,
  author       = {Smaldino, Paul E. and McElreath, Richard},
  title        = {The natural selection of bad science},
  journaltitle = {Royal Society Open Science},
  date         = {2016-06},
  volume       = {3},
  number       = {9},
  pages        = {160384},
  doi          = {10.1098/rsos.160384},
  publisher    = {The Royal Society},
  timestamp    = {2017.03.20},
}

@Article{BafumiGelmanParkEtAl2005a,
  author       = {Bafumi, Joseph and Gelman, Andrew and Park, David K. and Kaplan, Noah},
  title        = {Practical issues in implementing and understanding {Bayesian} ideal point estimation},
  journaltitle = {Political Analysis},
  date         = {2005},
  volume       = {13},
  number       = {02},
  pages        = {171--187},
  doi          = {10.1093/pan/mpi010},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{Spirling2007a,
  author       = {Spirling, Arthur},
  title        = {{Bayesian} approaches for limited dependent variable change point problems},
  journaltitle = {Political Analysis},
  date         = {2007},
  volume       = {15},
  number       = {04},
  pages        = {387--405},
  doi          = {10.1093/pan/mpm022},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{ImaiLuStrauss2008a,
  author       = {Imai, Kosuke and Lu, Ying and Strauss, Aaron},
  title        = {{Bayesian} and {Likelihood} inference for 2×2 ecological tables: an incomplete-data approach},
  journaltitle = {Political Analysis},
  date         = {2008},
  volume       = {16},
  number       = {01},
  pages        = {41--69},
  doi          = {10.1093/pan/mpm017},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{Jackman2005b,
  author    = {Simon Jackman},
  title     = {Pooling the polls over an election campaign},
  journal   = {Australian Journal of Political Science},
  year      = {2005},
  volume    = {40},
  number    = {4},
  month     = dec,
  pages     = {499--517},
  doi       = {10.1080/10361140500302472},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.01},
}

@Article{RanganathGerrishBlei2014a,
  author        = {Ranganath, R. and Gerrish, S. and Blei, D. M.},
  title         = {{Black box variational inference}},
  journal       = {ArXiv e-prints},
  year          = {2014},
  month         = dec,
  eprint        = {1401.0118},
  url           = {https://arxiv.org/abs/1401.0118},
  adsnote       = {Provided by the SAO/NASA Astrophysics Data System},
  adsurl        = {http://adsabs.harvard.edu/abs/2014arXiv1401.0118R},
  archiveprefix = {arXiv},
  primaryclass  = {stat.ML},
}

@Article{LockGelman2010a,
  author       = {Lock, Kari and Gelman, Andrew},
  title        = {{Bayesian} combination of state polls and election forecasts},
  journaltitle = {Political Analysis},
  date         = {2010},
  volume       = {18},
  number       = {03},
  pages        = {337--348},
  doi          = {10.1093/pan/mpq002},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{MontgomeryNyhan2010a,
  author       = {Montgomery, Jacob M. and Nyhan, Brendan},
  title        = {{Bayesian} model averaging: theoretical developments and practical applications},
  journaltitle = {Political Analysis},
  date         = {2010},
  volume       = {18},
  number       = {02},
  pages        = {245--270},
  doi          = {10.1093/pan/mpq001},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{Quinn2004a,
  author       = {Quinn, Kevin M.},
  title        = {{Bayesian} factor analysis for mixed ordinal and continuous responses},
  journaltitle = {Political Analysis},
  date         = {2004},
  volume       = {12},
  number       = {04},
  pages        = {338--353},
  doi          = {10.1093/pan/mph022},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{ParkGelmanBafumi2004a,
  author       = {Park, David K. and Gelman, Andrew and Bafumi, Joseph},
  title        = {{Bayesian} multilevel estimation with poststratification: state-level estimates from national polls},
  journaltitle = {Political Analysis},
  date         = {2004},
  volume       = {12},
  number       = {04},
  pages        = {375--385},
  doi          = {10.1093/pan/mph024},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{BakkerPoole2013a,
  author       = {Bakker, Ryan and Poole, Keith T.},
  title        = {{Bayesian} Metric Multidimensional Scaling},
  journaltitle = {Political Analysis},
  date         = {2013},
  volume       = {21},
  number       = {01},
  pages        = {125--140},
  doi          = {10.1093/pan/mps039},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-14},
}

@Article{Martin2003a,
  author    = {Andrew D. Martin},
  title     = {Bayesian Inference for Heterogeneous Event Counts},
  journal   = {Sociological Methods {\&} Research},
  year      = {2003},
  volume    = {32},
  number    = {1},
  month     = aug,
  pages     = {30--63},
  doi       = {10.1177/0049124103253500},
  publisher = {{SAGE} Publications},
  timestamp = {2018.05.01},
}

@Article{MontgomeryHollenbachWard2012a,
  author       = {Montgomery, Jacob M. and Hollenbach, Florian M. and Ward, Michael D.},
  title        = {Improving predictions using ensemble {Bayesian} model averaging},
  journaltitle = {Political Analysis},
  date         = {2012},
  volume       = {20},
  number       = {03},
  pages        = {271--291},
  doi          = {10.1093/pan/mps002},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{KruschkeLiddell2017a,
  author       = {Kruschke, John K. and Liddell, Torrin M.},
  title        = {The {Bayesian} new statistics: hypothesis testing, estimation, meta-analysis, and power analysis from a {Bayesian} perspective},
  journaltitle = {Psychonomic Bulletin \& Review},
  date         = {2017-02},
  doi          = {10.3758/s13423-016-1221-4},
  publisher    = {Springer Nature},
  timestamp    = {2017-05-21},
}

@Article{Kruschke2013a,
  author       = {Kruschke, John K.},
  title        = {{Bayesian} estimation supersedes the {t} test.},
  journaltitle = {Journal of Experimental Psychology: General},
  date         = {2013},
  volume       = {142},
  number       = {2},
  pages        = {573--603},
  doi          = {10.1037/a0029146},
  publisher    = {American Psychological Association (APA)},
  timestamp    = {2017-05-14},
}

@Book{Jeliazkov2014a,
  author    = {Jeliazkov, Ivan},
  title     = {{Bayesian} inference in the social sciences},
  year      = {2014},
  date      = {2014-10-31},
  publisher = {Wiley},
  isbn      = {1118771214},
  pagetotal = {352},
  ean       = {9781118771211},
  timestamp = {2017-05-14},
}

@Article{GelmanShalizi2012a,
  author       = {Gelman, Andrew and Shalizi, Cosma Rohilla},
  title        = {Philosophy and the practice of {Bayesian} statistics},
  journaltitle = {British Journal of Mathematical and Statistical Psychology},
  date         = {2012-02},
  volume       = {66},
  number       = {1},
  pages        = {8--38},
  doi          = {10.1111/j.2044-8317.2011.02037.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Rubin1984a,
  author       = {Rubin, Donald B.},
  title        = {{Bayesianly} Justifiable and Relevant Frequency Calculations for the Applied Statistician},
  journaltitle = {The Annals of Statistics},
  date         = {1984-12},
  volume       = {12},
  number       = {4},
  pages        = {1151--1172},
  doi          = {10.1214/aos/1176346785},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{Berger2003a,
  author       = {Berger, James O.},
  title        = {Could {Fisher}, {Jeffreys} and {Neyman} Have Agreed on Testing?},
  journaltitle = {Statistical Science},
  date         = {2003-02},
  volume       = {18},
  number       = {1},
  pages        = {1--32},
  doi          = {10.1214/ss/1056397485},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{BergerSellke1987a,
  author       = {Berger, James O. and Sellke, Thomas},
  title        = {Testing a point null hypothesis: the irreconcilability of p values and evidence},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1987-03},
  volume       = {82},
  number       = {397},
  pages        = {112},
  doi          = {10.2307/2289131},
  publisher    = {JSTOR},
}

@Book{Kaplan2014a,
  author    = {Kaplan, David},
  title     = {{Bayesian} statistics for the social sciences},
  year      = {2014},
  date      = {2014-07-16},
  publisher = {Guilford Press},
  pagetotal = {318},
  ean       = {9781462516674},
  timestamp = {2017-05-14},
}

@Article{HumphreysJacobs2015a,
  author       = {Humphreys, Macartan and Jacobs, Alan M.},
  title        = {Mixing methods: a {Bayesian} approach},
  journaltitle = {American Political Science Review},
  date         = {2015-11},
  volume       = {109},
  number       = {04},
  pages        = {653--673},
  doi          = {10.1017/s0003055415000453},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Book{Lynch2007a,
  title     = {Introduction to applied {Bayesian} statistics and estimation for social scientists},
  date      = {2007},
  editor    = {Lynch, Scott M.},
  publisher = {Springer Nature},
  doi       = {10.1007/978-0-387-71265-9},
  timestamp = {2017-05-21},
}

@Article{Darmofal2009a,
  author       = {Darmofal, David},
  title        = {{Bayesian} spatial survival models for political event processes},
  journaltitle = {American Journal of Political Science},
  date         = {2009-01},
  volume       = {53},
  number       = {1},
  pages        = {241--257},
  doi          = {10.1111/j.1540-5907.2008.00368.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{RosasShomerHaptonstahl2014a,
  author       = {Rosas, Guillermo and Shomer, Yael and Haptonstahl, Stephen R.},
  title        = {No news is news: nonignorable nonresponse in roll-call data analysis},
  journaltitle = {American Journal of Political Science},
  date         = {2014-08},
  volume       = {59},
  number       = {2},
  pages        = {511--528},
  doi          = {10.1111/ajps.12148},
  publisher    = {Wiley-Blackwell},
}

@Article{Stegmueller2013a,
  author       = {Stegmueller, Daniel},
  title        = {How many countries for multilevel modeling? a comparison of frequentist and {Bayesian} approaches},
  journaltitle = {American Journal of Political Science},
  date         = {2013-01},
  volume       = {57},
  number       = {3},
  pages        = {748--761},
  doi          = {10.1111/ajps.12001},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-14},
}

@Article{HareArmstrongBakkerEtAl2014a,
  author       = {Hare, Christopher and Armstrong, David A. and Bakker, Ryan and Carroll, Royce and Poole, Keith T.},
  title        = {Using {Bayesian} {Aldrich-McKelvey} scaling to study citizens’ ideological preferences and perceptions},
  journaltitle = {American Journal of Political Science},
  date         = {2014-09},
  volume       = {59},
  number       = {3},
  pages        = {759--774},
  doi          = {10.1111/ajps.12151},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{HonakerKing2010a,
  author       = {Honaker, James and King, Gary},
  title        = {What to do about missing values in time-series cross-section data},
  journaltitle = {American Journal of Political Science},
  date         = {2010-04},
  volume       = {54},
  number       = {2},
  pages        = {561--581},
  doi          = {10.1111/j.1540-5907.2010.00447.x},
  publisher    = {Wiley-Blackwell},
}

@Article{Gelfand1998a,
  author    = {A. Gelfand},
  title     = {Model choice: a minimum posterior predictive loss approach},
  journal   = {Biometrika},
  year      = {1998},
  volume    = {85},
  number    = {1},
  month     = mar,
  pages     = {1--11},
  doi       = {10.1093/biomet/85.1.1},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018.05.01},
}

@Article{Park2010a,
  author       = {Park, Jong Hee},
  title        = {Structural change in {U.S.} presidents’ use of force},
  journaltitle = {American Journal of Political Science},
  date         = {2010-06},
  volume       = {54},
  number       = {3},
  pages        = {766--782},
  doi          = {10.1111/j.1540-5907.2010.00459.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Jackman2001a,
  author    = {Simon Jackman},
  title     = {Multidimensional analysis of roll call data via {Bayesian} simulation: identification, estimation, inference, and model checking},
  journal   = {Political Analysis},
  year      = {2001},
  volume    = {9},
  number    = {3},
  pages     = {227--241},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791646},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.01},
}

@Article{Gross2014a,
  author       = {Gross, Justin H.},
  title        = {Testing what matters (if you must test at all): a context-driven approach to substantive and statistical significance},
  journaltitle = {American Journal of Political Science},
  date         = {2014-11},
  volume       = {59},
  number       = {3},
  pages        = {775--788},
  doi          = {10.1111/ajps.12149},
  publisher    = {Wiley-Blackwell},
}

@Article{WawroKatznelson2013a,
  author       = {Wawro, Gregory J. and Katznelson, Ira},
  title        = {Designing historical social scientific inquiry: how parameter heterogeneity can bridge the methodological divide between quantitative and qualitative approaches},
  journaltitle = {American Journal of Political Science},
  date         = {2013-08},
  volume       = {58},
  number       = {2},
  pages        = {526--546},
  doi          = {10.1111/ajps.12041},
  publisher    = {Wiley-Blackwell},
}

@Article{PopeTreier2011a,
  author       = {Pope, Jeremy C. and Treier, Shawn},
  title        = {Reconsidering the great compromise at the {Federal} {Convention} of 1787: deliberation and agenda effects on the {Senate} and slavery},
  journaltitle = {American Journal of Political Science},
  date         = {2011-01},
  volume       = {55},
  number       = {2},
  pages        = {289--306},
  doi          = {10.1111/j.1540-5907.2010.00490.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{TreierJackman2008a,
  author       = {Treier, Shawn and Jackman, Simon},
  title        = {Democracy as a latent variable},
  journaltitle = {American Journal of Political Science},
  date         = {2008-01},
  volume       = {52},
  number       = {1},
  pages        = {201--217},
  doi          = {10.1111/j.1540-5907.2007.00308.x},
  publisher    = {Wiley-Blackwell},
}

@Article{WesternJackman1994a,
  author       = {Western, Bruce and Jackman, Simon},
  title        = {{Bayesian} inference for comparative research},
  journaltitle = {American Political Science Review},
  date         = {1994-06},
  volume       = {88},
  number       = {02},
  pages        = {412--423},
  doi          = {10.2307/2944713},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{ClintonJackmanRivers2004a,
  author       = {Clinton, Joshua and Jackman, Simon and Rivers, Douglas},
  title        = {The statistical analysis of roll call data},
  journaltitle = {American Political Science Review},
  date         = {2004-05},
  volume       = {98},
  number       = {02},
  pages        = {355--370},
  doi          = {10.1017/s0003055404001194},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017.03.22},
}

@Article{ShihAdolphLiu2012a,
  author       = {Shih, Victor and Adolph, Christopher and Liu, Mingxing},
  title        = {Getting ahead in the {Communist} {Party}: explaining the advancement of {Central} {Committee} members in {China}},
  journaltitle = {American Political Science Review},
  date         = {2012-02},
  volume       = {106},
  number       = {01},
  pages        = {166--187},
  doi          = {10.1017/s0003055411000566},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Book{RasmussenWilliam2006a,
  author    = {Rasmussen, Carl Edward and William, Christopher K. I.},
  title     = {{Gaussian} processes for machine learning},
  year      = {2006},
  date      = {2006-01-11},
  publisher = {MIT University Press Group Ltd},
  isbn      = {026218253X},
  ean       = {9780262182539},
  timestamp = {2017-05-21},
}

@Book{Berger1993a,
  author    = {Berger, James O.},
  title     = {Statistical decision theory and {Bayesian} analysis},
  year      = {1993},
  date      = {1993-03-25},
  publisher = {Springer},
  isbn      = {0387960988},
  pagetotal = {640},
  ean       = {9780387960982},
  timestamp = {2017-05-21},
}

@Book{Downey2013a,
  author    = {Downey, Allan B.},
  title     = {Think {Bayes}},
  date      = {2013},
  edition   = {1},
  publisher = {OŔeilly Media},
  isbn      = {978-1-449-37078-7},
  url       = {http://greenteapress.com/wp/think-bayes/},
  timestamp = {2017-05-14},
}

@Article{Eddy2004a,
  author       = {Eddy, Sean R.},
  title        = {What is {Bayesian} statistics?},
  journaltitle = {Nature Biotechnology},
  date         = {2004-09},
  volume       = {22},
  number       = {9},
  pages        = {1177--1178},
  doi          = {10.1038/nbt0904-1177},
  publisher    = {Springer Nature},
  timestamp    = {2017-05-21},
}

@Article{PugaKrzywinskiAltman2015a,
  author       = {Puga, Jorge López and Krzywinski, Martin and Altman, Naomi},
  title        = {Points of significance: {Bayesian} networks},
  journaltitle = {Nature Methods},
  date         = {2015-08},
  volume       = {12},
  number       = {9},
  pages        = {799--800},
  doi          = {10.1038/nmeth.3550},
  publisher    = {Springer Nature},
  timestamp    = {2017-03-24},
}

@Article{PugaKrzywinskiAltman2015b,
  author       = {Puga, Jorge López and Krzywinski, Martin and Altman, Naomi},
  title        = {Points of significance: {Bayes’} theorem},
  journaltitle = {Nature Methods},
  date         = {2015-03},
  volume       = {12},
  number       = {4},
  pages        = {277--278},
  doi          = {10.1038/nmeth.3335},
  publisher    = {Springer Nature},
  timestamp    = {2017-05-21},
}

@Unpublished{OldfordCherry2006a,
  author       = {Oldford, R. W. and Cherry, W. H.},
  title        = {Picturing probability: the poverty of {Venn} diagrams, the richness of eikosograms},
  date         = {2006-10-12},
  howpublished = {working paper},
  url          = {http://sas.uwaterloo.ca/~rwoldfor/papers/venn/eikosograms/paperpdf.pdf},
  urldate      = {2006-10-12},
  timestamp    = {2017-05-21},
}

@Article{BorsboomHaig2012a,
  author       = {Borsboom, Denny and Haig, Brian D.},
  title        = {How to practise {Bayesian} statistics outside the {Bayesian} church: What philosophy for {Bayesian} statistical modelling?},
  journaltitle = {British Journal of Mathematical and Statistical Psychology},
  date         = {2012-10},
  volume       = {66},
  number       = {1},
  pages        = {39--44},
  doi          = {10.1111/j.2044-8317.2012.02062.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Prentice1976a,
  author    = {Ross L. Prentice},
  title     = {A Generalization of the Probit and Logit Methods for Dose Response Curves},
  journal   = {Biometrics},
  year      = {1976},
  volume    = {32},
  number    = {4},
  pages     = {761--768},
  issn      = {0006341X},
  url       = {http://www.jstor.org/stable/2529262},
  abstract  = {The relationship between response probability and dosage in quantal response bioassay is modelled using a four parameter class. In addition to location and scale quantities the model includes two shape parameters that essentially index skewness and heaviness of tails of the dose-response curve. The class of models includes such special cases as the logistic, normal, extreme minimum value, extreme maximum value, double exponential, exponential and reflected exponential distribution functions. Score tests are derived for logistic and normal hypotheses and certain submodels are discussed for which the model fitting is computationally convenient. The data of Bliss [1935] illustrates the potential improvement over usual methods in the estimation of critical dose levels.},
  publisher = {[Wiley, International Biometric Society]},
  timestamp = {2018.05.01},
}

@Article{GelmanShalizi2012b,
  author       = {Gelman, Andrew and Shalizi, Cosma},
  title        = {Rejoinder to discussion of ‘philosophy and the practice of {Bayesian} statistics’},
  journaltitle = {British Journal of Mathematical and Statistical Psychology},
  date         = {2012-10},
  volume       = {66},
  number       = {1},
  pages        = {76--80},
  doi          = {10.1111/j.2044-8317.2012.02066.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{CarpenterGelmanHoffmanEtAl2017a,
  author       = {Carpenter, Bob and Gelman, Andrew and Hoffman, Matthew D. and Lee, Daniel and Goodrich, Ben and Betancourt, Michael and Brubaker, Marcus and Guo, Jiqiang and Li, Peter and Riddell, Allen},
  title        = {{Stan}: a probabilistic programming language},
  journaltitle = {Journal of Statistical Software},
  date         = {2017},
  volume       = {76},
  number       = {1},
  doi          = {10.18637/jss.v076.i01},
  publisher    = {Foundation for Open Access Statistic},
  timestamp    = {2017-05-21},
}

@Article{PiironenVehtari2015a,
  author      = {Piironen, Juho and Vehtari, Aki},
  title       = {Projection predictive model selection for {Gaussian} processes},
  date        = {2015-10-16},
  doi         = {10.1109/MLSP.2016.7738829},
  eprint      = {1510.04813v3},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1510.04813v3:PDF},
  keywords    = {stat.ME},
  timestamp   = {2017-05-21},
}

@Article{GelmanVehtariJylaenkiEtAl2014a,
  author      = {Gelman, Andrew and Vehtari, Aki and Jylänki, Pasi and Sivula, Tuomas and Tran, Dustin and Sahai, Swupnil and Blomstedt, Paul and Cunningham, John P. and Schiminovich, David and Robert, Christian},
  title       = {Expectation propagation as a way of life: A framework for {Bayesian} inference on partitioned data},
  date        = {2014-12-16},
  eprint      = {1412.4869v2},
  eprintclass = {stat.CO},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1412.4869v2:PDF},
  keywords    = {stat.CO, stat.ME, stat.ML},
  timestamp   = {2017-05-21},
}

@Article{VehtariLampinen2002a,
  author       = {Vehtari, Aki and Lampinen, Jouko},
  title        = {{Bayesian} Model Assessment and Comparison Using Cross-Validation Predictive Densities},
  journaltitle = {Neural Computation},
  date         = {2002-10},
  volume       = {14},
  number       = {10},
  pages        = {2439--2468},
  doi          = {10.1162/08997660260293292},
  publisher    = {MIT Press - Journals},
  timestamp    = {2017-05-21},
}

@Article{CookGelmanRubin2006a,
  author       = {Cook, Samantha R. and Gelman, Andrew and Rubin, Donald B.},
  title        = {Validation of Software for {Bayesian} Models Using Posterior Quantiles},
  journaltitle = {Journal of Computational and Graphical Statistics},
  date         = {2006-09},
  volume       = {15},
  number       = {3},
  pages        = {675--692},
  doi          = {10.1198/106186006x136976},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-05-21},
}

@Article{Gelfand1998b,
  author    = {A. Gelfand},
  title     = {Model choice: a minimum posterior predictive loss approach},
  journal   = {Biometrika},
  year      = {1998},
  volume    = {85},
  number    = {1},
  month     = mar,
  pages     = {1--11},
  doi       = {10.1093/biomet/85.1.1},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018.05.02},
}

@Article{Jackman2004a,
  author       = {Jackman, Simon},
  title        = {{Bayesian} Analysis for Political Research},
  journaltitle = {Annual Review of Political Science},
  date         = {2004-05},
  volume       = {7},
  number       = {1},
  pages        = {483--505},
  doi          = {10.1146/annurev.polisci.7.012003.104706},
  publisher    = {Annual Reviews},
  timestamp    = {2017-05-21},
}

@Article{WardBeger2017a,
  author       = {Ward, Michael D. and Beger, Andreas},
  title        = {Lessons from near real-time forecasting of irregular leadership changes},
  journaltitle = {Journal of Peace Research},
  date         = {2017-03},
  editor       = {Hegre, Håvard and Metternich, Nils W. and Nygård, Håvard Mokleiv and Wucherpfennig, Julian},
  volume       = {54},
  number       = {2},
  pages        = {141--156},
  doi          = {10.1177/0022343316680858},
  publisher    = {SAGE Publications},
  timestamp    = {2017-03-24},
}

@Article{Western1998a,
  author       = {Western, Bruce},
  title        = {Causal Heterogeneity in Comparative Research: A {Bayesian} Hierarchical Modelling Approach},
  journaltitle = {American Journal of Political Science},
  date         = {1998},
  volume       = {42},
  number       = {4},
  pages        = {1233--1259},
  doi          = {10.2307/2991856},
  url          = {http://www.jstor.org/stable/2991856},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-21},
}

@Book{Kahneman2013a,
  author    = {Kahneman, Daniel},
  title     = {Thinking, Fast and Slow},
  year      = {2013},
  date      = {2013-04-11},
  publisher = {Macmillan USA},
  isbn      = {0374533555},
  pagetotal = {499},
  ean       = {9780374533557},
  timestamp = {2017.03.23},
}

@Book{KahnemanSlovicTversky1982a,
  title     = {Judgment Under Uncertainty},
  year      = {1982},
  date      = {1982-05-11},
  editor    = {Kahneman, Daniel and Slovic, Paul and Tversky, Amos},
  publisher = {Cambridge University Pr.},
  isbn      = {0521284147},
  ean       = {9780521284141},
  timestamp = {2017.03.23},
}

@Article{SpiegelhalterRice2009a,
  author       = {Spiegelhalter, D. and Rice, K.},
  title        = {{Bayesian} statistics},
  journaltitle = {Scholarpedia},
  date         = {2009},
  volume       = {4},
  number       = {8},
  pages        = {5230},
  note         = {revision 91036},
  url          = {http://www.scholarpedia.org/article/Bayesian_statistics},
  urldate      = {2017-03-23},
  timestamp    = {2017-05-21},
}

@Article{LuoJiao2017a,
  author    = {Luo, Yong and Jiao, Hong},
  title     = {Using the {Stan} Program for {Bayesian} Item Response Theory},
  journal   = {Educational and Psychological Measurement},
  year      = {2017},
  month     = feb,
  pages     = {001316441769366},
  doi       = {10.1177/0013164417693666},
  publisher = {{SAGE} Publications},
  timestamp = {2018.05.01},
}

@Article{CaiChoiHansenEtAl2016a,
  author       = {Cai, Li and Choi, Kilchan and Hansen, Mark and Harrell, Lauren},
  title        = {Item Response Theory},
  journaltitle = {Annual Review of Statistics and Its Application},
  date         = {2016-06},
  volume       = {3},
  number       = {1},
  pages        = {297--321},
  doi          = {10.1146/annurev-statistics-041715-033702},
  publisher    = {Annual Reviews},
  timestamp    = {2017-03-24},
}

@Article{LaverBenoitGarry2003a,
  author       = {Laver, Michael and Benoit, Kenneth and Garry, John},
  title        = {Extracting Policy Positions from Political Texts Using Words as Data},
  journaltitle = {The American Political Science Review},
  date         = {2003},
  volume       = {97},
  number       = {2},
  pages        = {311--331},
  issn         = {0003-0554},
  url          = {http://www.jstor.org/stable/3118211},
  publisher    = {[American Political Science Association, Cambridge University Press]},
  timestamp    = {2017-03-24},
}

@Article{Jackman2005c,
  author    = {Simon Jackman},
  title     = {Pooling the polls over an election campaign},
  journal   = {Australian Journal of Political Science},
  year      = {2005},
  volume    = {40},
  number    = {4},
  month     = dec,
  pages     = {499--517},
  doi       = {10.1080/10361140500302472},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.02},
}

@Article{GleditschRuggeri2010a,
  author       = {Gleditsch, Kristian Skrede and Ruggeri, Andrea},
  title        = {Political opportunity structures, democracy, and civil war},
  journaltitle = {Journal of Peace Research},
  date         = {2010-05},
  volume       = {47},
  number       = {3},
  month        = may,
  pages        = {299--310},
  doi          = {10.1177/0022343310362293},
  publisher    = {SAGE Publications},
  timestamp    = {2017-03-24},
}

@Article{Chen2013a,
  author       = {Chen, M. Keith},
  title        = {The Effect of Language on Economic Behavior: Evidence from Savings Rates, Health Behaviors, and Retirement Assets},
  journaltitle = {American Economic Review},
  date         = {2013-04},
  volume       = {103},
  number       = {2},
  pages        = {690--731},
  doi          = {10.1257/aer.103.2.690},
  publisher    = {American Economic Association},
}

@Unpublished{GentzkowShapiro2014a,
  author    = {Gentzkow, Matthew and Shapiro, Jesse M.},
  title     = {Code and Data for the Social Sciences: A Practitioner’s Guid},
  date      = {2014-03-10},
  url       = {https://people.stanford.edu/gentzkow/sites/default/files/codeanddata.pdf},
  urldate   = {2017-03-23},
  timestamp = {2017.03.23},
}

@Article{PetreWilson2014a,
  author      = {Petre, Marian and Wilson, Greg},
  title       = {Code review for and by scientists},
  date        = {2014-07-21},
  eprint      = {1407.5648v2},
  eprintclass = {cs.SE},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1407.5648v2:PDF},
  keywords    = {cs.SE},
}

@Article{Goodman1954a,
  author       = {Goodman, Leo A.},
  title        = {Some practical techniques in serial number analysis},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1954-03},
  volume       = {49},
  number       = {265},
  pages        = {97--112},
  doi          = {10.1080/01621459.1954.10501218},
  publisher    = {Informa UK Limited},
}

@Article{Johnson1994a,
  author       = {Johnson, Roger W.},
  title        = {Estimating the size of a population},
  journaltitle = {Teaching Statistics},
  date         = {1994-06},
  volume       = {16},
  number       = {2},
  pages        = {50--52},
  doi          = {10.1111/j.1467-9639.1994.tb00688.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-03-24},
}

@Article{AlbertAnderson1984a,
  author    = {Albert, A. and Anderson, J. A.},
  title     = {On the existence of maximum likelihood estimates in logistic regression models},
  journal   = {Biometrika},
  year      = {1984},
  volume    = {71},
  number    = {1},
  pages     = {1--10},
  doi       = {10.1093/biomet/71.1.1},
  eprint    = {/oup/backfile/content_public/journal/biomet/71/1/10.1093/biomet/71.1.1/2/71-1-1.pdf},
  timestamp = {2018.05.01},
}

@Article{Taddy2013a,
  author       = {Taddy, Matt},
  title        = {Multinomial inverse regression for text analysis},
  journaltitle = {Journal of the American Statistical Association},
  date         = {2013-09},
  volume       = {108},
  number       = {503},
  pages        = {755--770},
  doi          = {10.1080/01621459.2012.734168},
  publisher    = {Informa UK Limited},
  timestamp    = {2017.03.23},
}

@Article{Taddy2015a,
  author      = {Taddy, Matt},
  title       = {Document classification by inversion of distributed language representations},
  date        = {2015-04-27},
  eprint      = {1504.07295v3},
  eprintclass = {cs.CL},
  eprinttype  = {arXiv},
  url         = {https://arxiv.org/pdf/1504.07295v3.pdf},
  file        = {online:http\://arxiv.org/pdf/1504.07295v3:PDF},
  keywords    = {cs.CL, cs.IR, stat.AP},
  timestamp   = {2017.03.23},
}

@Article{MostellerWallace1963a,
  author       = {Mosteller, Frederick and Wallace, David L.},
  title        = {Inference in an authorship problem},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1963-06},
  volume       = {58},
  number       = {302},
  pages        = {275--309},
  doi          = {10.1080/01621459.1963.10500849},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{GillSpirling2015a,
  author       = {Gill, Michael and Spirling, Arthur},
  title        = {Estimating the severity of the {Leaks} {U.S.} diplomatic cables disclosure},
  journaltitle = {Political Analysis},
  date         = {2015},
  volume       = {23},
  number       = {02},
  pages        = {299--305},
  doi          = {10.1093/pan/mpv005},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{CarvalhoJohannesLopesEtAl2010a,
  author       = {Carvalho, Carlos M. and Johannes, Michael S. and Lopes, Hedibert F. and Polson, Nicholas G.},
  title        = {Particle learning and smoothing},
  journaltitle = {Statistical Science},
  year         = {2010},
  volume       = {25},
  number       = {1},
  month        = feb,
  pages        = {88--106},
  doi          = {10.1214/10-STS325},
  publisher    = {The Institute of Mathematical Statistics},
  timestamp    = {2018.05.01},
}

@Article{MonroeColaresiQuinn2008a,
  author       = {Monroe, Burt L. and Colaresi, Michael P. and Quinn, Kevin M.},
  title        = {Fightin’ words: lexical feature selection and evaluation for identifying the content of political conflict},
  journaltitle = {Political Analysis},
  date         = {2008},
  volume       = {16},
  number       = {04},
  pages        = {372--403},
  doi          = {10.1093/pan/mpn018},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{Efron1986a,
  author       = {Efron, B.},
  title        = {Why isn’t everyone a {Bayesian}?},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {1--5},
  doi          = {10.1080/00031305.1986.10475342},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-05-21},
}

@Article{Chernoff1986a,
  author       = {Chernoff, Herman},
  title        = {Comment},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {5--6},
  doi          = {10.1080/00031305.1986.10475343},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{Lindley1986a,
  author       = {Lindley, D. V.},
  title        = {Comment},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {6--7},
  doi          = {10.1080/00031305.1986.10475344},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{Morris1986a,
  author       = {Morris, C. N.},
  title        = {Comment},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {7--8},
  doi          = {10.1080/00031305.1986.10475345},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{Smith1986a,
  author       = {Smith, Adrian F. M.},
  title        = {Comment},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {10--10},
  doi          = {10.1080/00031305.1986.10475347},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{Press1986a,
  author       = {Press, S. James},
  title        = {Comment},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {9--10},
  doi          = {10.1080/00031305.1986.10475346},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{Efron1986b,
  author       = {Efron, B.},
  title        = {Reply},
  journaltitle = {The American Statistician},
  date         = {1986-02},
  volume       = {40},
  number       = {1},
  pages        = {11--11},
  doi          = {10.1080/00031305.1986.10475348},
  publisher    = {Informa UK Limited},
}

@Article{PiironenVehtari2016b,
  author    = {Piironen, Juho and Vehtari, Aki},
  title     = {Comparison of {Bayesian} predictive methods for model selection},
  journal   = {Statistics and Computing},
  year      = {2016},
  volume    = {27},
  number    = {3},
  month     = apr,
  pages     = {711--735},
  doi       = {10.1007/s11222-016-9649-y},
  publisher = {Springer Nature},
  timestamp = {2018.05.01},
}

@Article{GhoshGhattas2015a,
  author       = {Ghosh, Joyee and Ghattas, Andrew E.},
  title        = {{Bayesian} variable selection under collinearity},
  journaltitle = {The American Statistician},
  date         = {2015-07},
  volume       = {69},
  number       = {3},
  pages        = {165--173},
  doi          = {10.1080/00031305.2015.1031827},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Book{RobertCasella2004a,
  author    = {Robert, Christian P. and Casella, George},
  title     = {{Monte} {Carlo} statistical methods},
  date      = {2004},
  publisher = {Springer New York},
  doi       = {10.1007/978-1-4757-4145-2},
  timestamp = {2017-03-24},
}

@Article{CasellaGeorge1992a,
  author       = {Casella, George and George, Edward I.},
  title        = {Explaining the {Gibbs} Sampler},
  journaltitle = {The American Statistician},
  date         = {1992-08},
  volume       = {46},
  number       = {3},
  pages        = {167--174},
  doi          = {10.1080/00031305.1992.10475878},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{AllisonDunkley2013a,
  author      = {Allison, Rupert and Dunkley, Joanna},
  title       = {Comparison of sampling techniques for {Bayesian} parameter estimation},
  date        = {2013-08-12},
  doi         = {10.1093/mnras/stt2190},
  eprint      = {1308.2675v2},
  eprintclass = {astro-ph.IM},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1308.2675v2:PDF},
  keywords    = {astro-ph.IM, astro-ph.CO},
  timestamp   = {2017-03-24},
}

@Article{Berger2006a,
  author       = {Berger, James},
  title        = {The case for objective {Bayesian} Analysis},
  journaltitle = {Bayesian Analysis},
  date         = {2006},
  volume       = {1},
  pages        = {385--402},
  doi          = {10.1214/06-ba115},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-03-24},
}

@InBook{Neal2012a,
  author      = {Neal, Radford M.},
  title       = {{MCMC} using {Hamiltonian} dynamics},
  booktitle   = {Handbook of {Markov} chain {Monte} {Carlo}},
  date        = {2012-06-09},
  chapter     = {5},
  eprint      = {1206.1901v1},
  eprintclass = {stat.CO},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1206.1901v1:PDF},
  keywords    = {stat.CO, physics.comp-ph},
  timestamp   = {2017-03-24},
}

@Article{SmithGelfand1992a,
  author       = {Smith, A. F. M. and Gelfand, A. E.},
  title        = {{Bayesian} Statistics without Tears: A Sampling/Resampling Perspective},
  journaltitle = {The American Statistician},
  date         = {1992-05},
  volume       = {46},
  number       = {2},
  pages        = {84--88},
  doi          = {10.1080/00031305.1992.10475856},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-03-24},
}

@Article{GelfandHillsRacine-PoonEtAl1990a,
  author       = {Gelfand, Alan E. and Hills, Susan E. and Racine-Poon, Amy and Smith, Adrian F. M.},
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  timestamp = {2018.05.01},
}

@Article{LiuChen1998a,
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  timestamp = {2018.05.02},
}

@Article{KingZeng2001a,
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  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-03-24},
}

@Article{KingZeng2001b,
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@TechReport{Hoehle2006a,
  author      = {Höhle, Held},
  title       = {{Bayesian} estimation of the size of a population},
  institution = {Sonderforschungsbereich 386},
  date        = {2006},
  type        = {techreport},
  number      = {499},
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@Book{MarinRobert2007a,
  author    = {Marin, Jean-Michel and Robert, Christian},
  title     = {{Bayesian} core: a practical approach to computational {Bayesian} statistics},
  year      = {2007},
  date      = {2007-05-26},
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@Article{Carpenter2017a,
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  journaltitle = {Stan Case Studies},
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@Article{CarpenterGabryGoodrich2017a,
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  journaltitle = {Stan Case Studies},
  date         = {2017-01-19},
  url          = {http://mc-stan.org/documentation/case-studies/pool-binary-trials-rstanarm.html},
  urldate      = {2017-04-15},
  timestamp    = {2017-04-15},
}

@Article{Betancourt2017a,
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  title        = {How the shape of a weakly informative prior affects inferences},
  journaltitle = {Stan Case Studies},
  date         = {2017-01},
  url          = {http://mc-stan.org/documentation/case-studies/weakly_informative_shapes.html},
  urldate      = {2017-04-15},
  timestamp    = {2017-04-15},
}

@Article{Betancourt2017b,
  author       = {Betancourt, Michael},
  title        = {Identifying {Bayesian} mixture models},
  journaltitle = {Stan Case Studies},
  year         = {2017},
  date         = {2017-02},
  timestamp    = {2017-05-21},
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@Article{Jackman2000a,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.01},
}

@Article{Carpenter2016a,
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  journaltitle = {Stan Case Studies},
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  urldate      = {2017-04-15},
  timestamp    = {2017-05-21},
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@Article{GelmanMengStern1996a,
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}

@Article{Statisticata,
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@WWW{Gelman2009a,
  author    = {Gelman, Andrew},
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  url       = {http://andrewgelman.com/2009/02/07/confusions_abou/},
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  timestamp = {2017-04-20},
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@Article{Gelman2014a,
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@Book{Stan2016a,
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@Article{SpiegelhalterBestCarlinEtAl2002a,
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@Article{KassRaftery1995a,
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@Article{GelmanHwangVehtari2013a,
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  volume       = {24},
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@Article{Kruschke2011a,
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  timestamp    = {2017-05-21},
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@Article{Kruschke2013b,
  author       = {Kruschke, John K.},
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  date         = {2013},
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@Article{FrielWyse2012a,
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@Article{FlegalHaranJones2008a,
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@Article{Betancourt2017c,
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  journaltitle = {Stan Case Studies},
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@Article{DielemanTemplin2014a,
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@Article{BellJones2014a,
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@Article{Stegmueller2013b,
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  volume       = {21},
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@Article{Rendon2012a,
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  publisher    = {Wiley-Blackwell},
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@Article{WickhamCookHofmannEtAl2010a,
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@Unpublished{Rainey2016b,
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  timestamp = {2017.04.25},
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@WWW{Goldera,
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  title     = {Interactions},
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  urldate   = {2017-03-21},
  timestamp = {2017.04.25},
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@Article{Jackman2000b,
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  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{ClarkLinzer2014a,
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@Article{BerryGolderMilton2012a,
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@Article{VehtariGelmanGabry2017a,
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  issn      = {1573-1375},
  doi       = {10.1007/s11222-016-9696-4},
  abstract  = {Leave-one-out cross-validation (LOO) and the widely applicable information criterion (WAIC) are methods for estimating pointwise out-of-sample prediction accuracy from a fitted Bayesian model using the log-likelihood evaluated at the posterior simulations of the parameter values. LOO and WAIC have various advantages over simpler estimates of predictive error such as AIC and DIC but are less used in practice because they involve additional computational steps. Here we lay out fast and stable computations for LOO and WAIC that can be performed using existing simulation draws. We introduce an efficient computation of LOO using Pareto-smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. Although WAIC is asymptotically equal to LOO, we demonstrate that PSIS-LOO is more robust in the finite case with weak priors or influential observations. As a byproduct of our calculations, we also obtain approximate standard errors for estimated predictive errors and for comparison of predictive errors between two models. We implement the computations in an R package called loo and demonstrate using models fit with the Bayesian inference package Stan.},
  day       = {01},
  timestamp = {2018.05.01},
}

@Article{AlvarezGarrettLange1991a,
  author    = {R. Michael Alvarez and Geoffrey Garrett and Peter Lange},
  title     = {Government partisanship, labor organization, and macroeconomic performance},
  journal   = {The American Political Science Review},
  year      = {1991},
  volume    = {85},
  number    = {2},
  pages     = {539--556},
  issn      = {00030554},
  url       = {http://www.jstor.org/stable/1963174},
  publisher = {[American Political Science Association, Cambridge University Press]},
  timestamp = {2018.05.01},
}

@Book{King1998a,
  author    = {King, Gary},
  title     = {Unifying Political Methodology: The {Likelihood} Theory of Statistical Inference},
  year      = {1998},
  date      = {1998-08-11},
  publisher = {UNIV OF MICHIGAN PR},
  isbn      = {0472085549},
  ean       = {9780472085545},
  timestamp = {2017-05-21},
}

@Article{GreenlandMansournia2015a,
  author       = {Greenland, Sander and Mansournia, Mohammad Ali},
  title        = {Penalization, bias reduction, and default priors in logistic and related categorical and survival regressions},
  journaltitle = {Statistics in Medicine},
  date         = {2015-05},
  volume       = {34},
  number       = {23},
  pages        = {3133--3143},
  doi          = {10.1002/sim.6537},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-04},
}

@Article{Gelfand1998c,
  author    = {A. Gelfand},
  title     = {Model choice: a minimum posterior predictive loss approach},
  journal   = {Biometrika},
  year      = {1998},
  volume    = {85},
  number    = {1},
  month     = mar,
  pages     = {1--11},
  doi       = {10.1093/biomet/85.1.1},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018.05.02},
}

@Article{KingTomzWittenberg2000a,
  author       = {King, Gary and Tomz, Michael and Wittenberg, Jason},
  title        = {Making the most of statistical analyses: improving interpretation and presentation},
  journaltitle = {American Journal of Political Science},
  date         = {2000-04},
  volume       = {44},
  number       = {2},
  pages        = {347},
  doi          = {10.2307/2669316},
  publisher    = {{JSTOR}},
  timestamp    = {2017-05-04},
}

@Article{Firth1993a,
  author       = {Firth, David},
  title        = {Bias reduction of maximum likelihood estimates},
  journaltitle = {Biometrika},
  date         = {1993},
  volume       = {80},
  number       = {1},
  pages        = {27--38},
  doi          = {10.1093/biomet/80.1.27},
  publisher    = {Oxford University Press ({OUP})},
  timestamp    = {2017.04.26},
}

@Article{BenoitPoel2017a,
  author       = {Benoit, Dries F. and den Poel, Dirk Van},
  title        = {{bayesQR}: A {Bayesian} approach to quantile regression},
  journaltitle = {Journal of Statistical Software},
  date         = {2017},
  volume       = {76},
  number       = {7},
  doi          = {10.18637/jss.v076.i07},
  publisher    = {Foundation for Open Access Statistic},
  timestamp    = {2017.04.28},
}

@Article{Jackman2000c,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{PolsonScott2012a,
  author       = {Polson, Nicholas G. and Scott, James G.},
  title        = {On the half-{Cauchy} prior for a global scale parameter},
  journaltitle = {Bayesian Analysis},
  date         = {2012-12},
  volume       = {7},
  number       = {4},
  pages        = {887--902},
  doi          = {10.1214/12-ba730},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-04},
}

@Article{GruenKosmidisZeileis2012a,
  author       = {Grün, Bettina and Kosmidis, Ioannis and Zeileis, Achim},
  title        = {Extended beta regression in {R}: shaken, stirred, mixed, and partitioned},
  journaltitle = {Journal of Statistical Software},
  date         = {2012},
  volume       = {48},
  number       = {11},
  doi          = {10.18637/jss.v048.i11},
  publisher    = {Foundation for Open Access Statistic},
  timestamp    = {2017.04.28},
}

@Article{Cribari-NetoZeileis2010a,
  author       = {Cribari-Neto, Francisco and Zeileis, Achim},
  title        = {Beta regression in {R}},
  journaltitle = {Journal of Statistical Software},
  date         = {2010},
  volume       = {34},
  number       = {2},
  doi          = {10.18637/jss.v034.i02},
  publisher    = {Foundation for Open Access Statistic},
  timestamp    = {2017-05-21},
}

@Article{Gelman2006a,
  author       = {Gelman, Andrew},
  title        = {Prior distributions for variance parameters in hierarchical models (comment on article by {Browne} and {Draper})},
  journaltitle = {Bayesian Analysis},
  date         = {2006-09},
  volume       = {1},
  number       = {3},
  pages        = {515--534},
  doi          = {10.1214/06-ba117a},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-04},
}

@Article{Jackman2001c,
  author    = {Simon Jackman},
  title     = {Multidimensional analysis of roll call data via {Bayesian} simulation: identification, estimation, inference, and model checking},
  journal   = {Political Analysis},
  year      = {2001},
  volume    = {9},
  number    = {3},
  pages     = {227--241},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791646},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{FerrariCribari-Neto2004a,
  author       = {Ferrari, Silvia and Cribari-Neto, Francisco},
  title        = {Beta regression for modelling rates and proportions},
  journaltitle = {Journal of Applied Statistics},
  date         = {2004-08},
  volume       = {31},
  number       = {7},
  pages        = {799--815},
  doi          = {10.1080/0266476042000214501},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-04},
}

@Article{BeckKatzTucker1998a,
  author       = {Beck, Nathaniel and Katz, Jonathan N. and Tucker, Richard},
  title        = {Taking time seriously: time-series-cross-section analysis with a binary dependent variable},
  journaltitle = {American Journal of Political Science},
  date         = {1998},
  volume       = {42},
  number       = {4},
  pages        = {1260--1288},
  url          = {http://www.jstor.org/stable/2991857},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-04},
}

@Article{Betancourt2016a,
  author      = {Betancourt, Michael},
  title       = {Diagnosing suboptimal cotangent disintegrations in {Hamiltonian} {Monte} {Carlo}},
  date        = {2016-04-03},
  eprint      = {1604.00695v1},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  url         = {http://arxiv.org/pdf/1604.00695v1:PDF},
  keywords    = {stat.ME},
  timestamp   = {2017-05-21},
}

@Article{BetancourtGirolami2013a,
  author      = {Betancourt, M. J. and Girolami, Mark},
  title       = {{Hamiltonian} {Monte} {Carlo} for hierarchical models},
  date        = {2013-12-03},
  eprint      = {1312.0906v1},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1312.0906v1:PDF},
  keywords    = {stat.ME},
  timestamp   = {2017-05-21},
}

@Article{EroshevaCurtis2017b,
  author    = {Elena A. Erosheva and S. McKay Curtis},
  title     = {Dealing with Reflection Invariance in Bayesian Factor Analysis},
  journal   = {Psychometrika},
  year      = {2017},
  month     = mar,
  doi       = {10.1007/s11336-017-9564-y},
  publisher = {Springer Nature},
  timestamp = {2018.05.02},
}

@Article{BelloniChernozhukovHansen2014a,
  author       = {Belloni, Alexandre and Chernozhukov, Victor and Hansen, Christian},
  title        = {High-dimensional methods and inference on structural and treatment effects},
  journaltitle = {Journal of Economic Perspectives},
  date         = {2014-05},
  volume       = {28},
  number       = {2},
  pages        = {29--50},
  doi          = {10.1257/jep.28.2.29},
  publisher    = {American Economic Association},
  timestamp    = {2017-05-04},
}

@Article{BelloniChenChernozhukovEtAl2012a,
  author       = {Belloni, A. and Chen, D. and Chernozhukov, V. and Hansen, C.},
  title        = {Sparse models and methods for optimal instruments with an application to eminent domain},
  journaltitle = {Econometrica},
  date         = {2012},
  volume       = {80},
  number       = {6},
  pages        = {2369--2429},
  doi          = {10.3982/ecta9626},
  publisher    = {The Econometric Society},
  timestamp    = {2017-05-04},
}

@Article{BhadraDattaPolsonEtAl2015a,
  author      = {Bhadra, Anindya and Datta, Jyotishka and Polson, Nicholas G. and Willard, Brandon},
  title       = {The horseshoe+ estimator of ultra-sparse signals},
  date        = {2015-02-02},
  eprint      = {1502.00560v2},
  eprintclass = {math.ST},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1502.00560v2:PDF},
  keywords    = {math.ST, stat.TH},
  timestamp   = {2017-05-21},
}

@Article{CarvalhoPolsonScott2010a,
  author       = {Carvalho, C. M. and Polson, N. G. and Scott, J. G.},
  title        = {The horseshoe estimator for sparse signals},
  journaltitle = {Biometrika},
  date         = {2010-04},
  volume       = {97},
  number       = {2},
  pages        = {465--480},
  doi          = {10.1093/biomet/asq017},
  publisher    = {Oxford University Press ({OUP})},
  timestamp    = {2017-05-21},
}

@Article{CarvalhoPolsonScott2009a,
  author    = {Carvalho, Carlos M. and Polson, Nicholas G. and Scott, James G.},
  title     = {Handling Sparsity via the horseshoe},
  date      = {2009},
  editor    = {van Dyk, David and Welling, Max},
  series    = {Proceedings of Machine Learning Research},
  volume    = {5},
  pages     = {73--80},
  url       = {http://proceedings.mlr.press/v5/carvalho09a.html},
  booktitle = {Proceedings of the Twelth International Conference on Artificial Intelligence and Statistics},
  file      = {carvalho09a.pdf:http\://proceedings.mlr.press/v5/carvalho09a/carvalho09a.pdf:PDF},
  location  = {Hilton Clearwater Beach Resort, Clearwater Beach, Florida USA},
  publisher = {PMLR},
  timestamp = {2017-05-21},
}

@Article{PasKleijnVaart2014a,
  author       = {van der Pas, S. L. and Kleijn, B. J. K. and van der Vaart, A. W.},
  title        = {The horseshoe estimator: posterior concentration around nearly black vectors},
  journaltitle = {Electronic Journal of Statistics},
  date         = {2014},
  volume       = {8},
  number       = {2},
  pages        = {2585--2618},
  doi          = {10.1214/14-ejs962},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@InCollection{PolsonScott2011a,
  author    = {Polson, Nicholas G. and Scott, James G.},
  title     = {Shrink globally, act locally: sparse {Bayesian} regularization and prediction},
  booktitle = {Bayesian Statistics},
  date      = {2011-10},
  publisher = {Oxford University Press},
  pages     = {501--538},
  doi       = {10.1093/acprof:oso/9780199694587.003.0017},
  timestamp = {2017-05-21},
}

@Article{GelmanRubin1992a,
  author       = {Gelman, Andrew and Rubin, Donald B.},
  title        = {Inference from iterative simulation using multiple sequences},
  journaltitle = {Statistical Science},
  date         = {1992},
  volume       = {7},
  number       = {4},
  pages        = {457--472},
  url          = {http://www.jstor.org/stable/2246093},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-04},
}

@Article{West1987a,
  author       = {West, Mike},
  title        = {On scale mixtures of normal distributions},
  journaltitle = {Biometrika},
  date         = {1987},
  volume       = {74},
  number       = {3},
  pages        = {646--648},
  doi          = {10.1093/biomet/74.3.646},
  publisher    = {Oxford University Press ({OUP})},
  timestamp    = {2017-05-01},
}

@Article{WardGreenhillBakke2010a,
  author       = {Ward, Michael D. and Greenhill, Brian D. and Bakke, Kristin M.},
  title        = {The perils of policy by {p}-value: Predicting civil conflicts},
  journaltitle = {Journal of Peace Research},
  date         = {2010-07},
  volume       = {47},
  number       = {4},
  pages        = {363--375},
  doi          = {10.1177/0022343309356491},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-14},
}

@Article{JuarezSteel2010a,
  author       = {Juárez, Miguel A. and Steel, Mark F. J.},
  title        = {Model-based clustering of non-{Gaussian} panel data based on skew-{t} distributions},
  journaltitle = {Journal of Business {\&} Economic Statistics},
  date         = {2010-01},
  volume       = {28},
  number       = {1},
  pages        = {52--66},
  doi          = {10.1198/jbes.2009.07145},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-14},
}

@Book{Martin1992a,
  author    = {Martin, Lisa},
  title     = {Coercive cooperation: explaining multilateral economic sanctions},
  date      = {1992},
  publisher = {Princeton University Press},
  isbn      = {978-0691086248},
  timestamp = {2017.05.01},
}

@Article{PiironenVehtari2016a,
  author      = {Piironen, Juho and Vehtari, Aki},
  title       = {On the hyperprior choice for the global shrinkage parameter in the horseshoe prior},
  date        = {2016-10-18},
  eprint      = {1610.05559v1},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1610.05559v1:PDF},
  keywords    = {stat.ME},
  timestamp   = {2017-05-21},
}

@Article{BlairBlattmanHartman2017a,
  author       = {Blair, Robert A. and Blattman, Christopher and Hartman, Alexandra},
  title        = {Predicting local violence},
  journaltitle = {Journal of Peace Research},
  date         = {2017-03},
  editor       = {Hegre, H{\aa}vard and Metternich, Nils W. and Nyg{\aa}rd, H{\aa}vard Mokleiv and Wucherpfennig, Julian},
  volume       = {54},
  number       = {2},
  pages        = {298--312},
  doi          = {10.1177/0022343316684009},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-14},
}

@Article{GhoshLiMitra2015a,
  author      = {Ghosh, Joyee and Li, Yingbo and Mitra, Robin},
  title       = {On the use of {Cauchy} prior distributions for {Bayesian} logistic regression},
  date        = {2015-07-26},
  eprint      = {1507.07170v2},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1507.07170v2:PDF},
  keywords    = {stat.ME},
  timestamp   = {2017-05-21},
}

@Article{BarrilleauxRainey2014a,
  author       = {Barrilleaux, Charles and Rainey, Carlisle},
  title        = {The Politics of Need},
  journaltitle = {State Politics {\&} Policy Quarterly},
  date         = {2014-12},
  volume       = {14},
  number       = {4},
  pages        = {437--460},
  doi          = {10.1177/1532440014561644},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-14},
}

@Article{VolinskyRafteryMadiganEtAl1999a,
  author       = {Volinsky, Chris T. and Raftery, Adrian E. and Madigan, David and Hoeting, Jennifer A.},
  title        = {{Bayesian} model averaging: a tutorial (with comments by {M.} {Clyde}, {David} {Draper} and {E.} {I.} {George}, and a rejoinder by the authors)},
  journaltitle = {Statistical Science},
  date         = {1999-11},
  volume       = {14},
  number       = {4},
  pages        = {382--417},
  doi          = {10.1214/ss/1009212519},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{FragosoNeto2015a,
  author      = {Fragoso, Tiago M. and Neto, Francisco Louzada},
  title       = {{Bayesian} model averaging: A systematic review and conceptual classification},
  date        = {2015-09-29},
  eprint      = {1509.08864v1},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  url         = {http://arxiv.org/pdf/1509.08864v1:PDF},
  keywords    = {stat.ME, stat.AP},
  timestamp   = {2017-05-21},
}

@Article{LeySteel2012a,
  author       = {Ley, Eduardo and Steel, Mark F. J.},
  title        = {Mixtures of {g}-priors for {Bayesian} model averaging with economic applications},
  journaltitle = {Journal of Econometrics},
  date         = {2012-12},
  volume       = {171},
  number       = {2},
  pages        = {251--266},
  doi          = {10.1016/j.jeconom.2012.06.009},
  publisher    = {Elsevier {BV}},
  timestamp    = {2017-05-21},
}

@Article{TobiasLi2004a,
  author       = {Tobias, Justin L. and Li, Mingliang},
  title        = {Returns to Schooling and {Bayesian} Model Averaging: A Union of Two Literatures},
  journaltitle = {Journal of Economic Surveys},
  date         = {2004-04},
  volume       = {18},
  number       = {2},
  pages        = {153--180},
  doi          = {10.1111/j.0950-0804.2004.00003.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Stigler2018a,
  author       = {Stigler, Stephen M.},
  title        = {{Richard} {Price}, the first {Bayesian}},
  journaltitle = {Statistical Science},
  year         = {2018},
  volume       = {33},
  number       = {1},
  month        = feb,
  pages        = {117--125},
  doi          = {10.1214/17-STS635},
  publisher    = {The Institute of Mathematical Statistics},
  timestamp    = {2018.05.01},
}

@Article{EfronMorris1975a,
  author       = {Efron, Bradley and Morris, Carl},
  title        = {Data analysis using {Stein’s} estimator and its generalizations},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1975-06},
  volume       = {70},
  number       = {350},
  pages        = {311--319},
  doi          = {10.1080/01621459.1975.10479864},
  publisher    = {Informa UK Limited},
  timestamp    = {2017.05.15},
}

@Article{RafteryHoetingVolinskyEtAl2017a,
  author    = {Raftery, Adrian and Hoeting, Jennifer and Volinsky, Chris and Painter, Ian and Yeung, Ka Yee},
  title     = {{BMA}: {Bayesian} model averaging},
  date      = {2017},
  note      = {R package version 3.18.7},
  url       = {https://CRAN.R-project.org/package=BMA},
  timestamp = {2017-05-14},
}

@Article{AminiShahramParmeterChristopher2011a,
  author       = {Amini Shahram, M. and Parmeter Christopher, F.},
  title        = {{Bayesian} model averaging in {R}},
  journaltitle = {Journal of Economic and Social Measurement},
  date         = {2011},
  volume       = {36},
  number       = {4},
  pages        = {253--287},
  issn         = {0747-9662},
  doi          = {10.3233/JEM-2011-0350},
  publisher    = {IOS Press},
  timestamp    = {2017-05-14},
}

@Article{IshwaranRao2005a,
  author       = {Ishwaran, Hemant and Rao, J. Sunil},
  title        = {Spike and slab variable selection: {Frequentist} and {Bayesian} strategies},
  journaltitle = {The Annals of Statistics},
  date         = {2005-04},
  volume       = {33},
  number       = {2},
  pages        = {730--773},
  doi          = {10.1214/009053604000001147},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@TechReport{BrockDurlaufWest2003a,
  author    = {Brock, William and Durlauf, Steven and West, Kenneth},
  title     = {Policy evaluation in uncertain economic environments},
  date      = {2003-10},
  doi       = {10.3386/w10025},
  publisher = {National Bureau of Economic Research},
  timestamp = {2017-05-21},
}

@Article{GeorgeMcCulloch1993a,
  author       = {George, Edward I. and McCulloch, Robert E.},
  title        = {Variable selection via {Gibbs} sampling},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1993-09},
  volume       = {88},
  number       = {423},
  pages        = {881--889},
  doi          = {10.1080/01621459.1993.10476353},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-21},
}

@Article{MitchellBeauchamp1988a,
  author       = {Mitchell, T. J. and Beauchamp, J. J.},
  title        = {{Bayesian} variable selection in linear regression},
  journaltitle = {Journal of the American Statistical Association},
  date         = {1988-12},
  volume       = {83},
  number       = {404},
  pages        = {1023--1032},
  doi          = {10.1080/01621459.1988.10478694},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-21},
}

@Article{HoerlKennard1970a,
  author       = {Hoerl, Arthur E. and Kennard, Robert W.},
  title        = {Ridge regression: biased estimation for nonorthogonal problems},
  journaltitle = {Technometrics},
  date         = {1970-02},
  volume       = {12},
  number       = {1},
  pages        = {55--67},
  doi          = {10.1080/00401706.1970.10488634},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-21},
}

@Unpublished{Zeugner2011a,
  author       = {Zeugner, Stefan},
  title        = {{Bayesian} model averaging with {BMS} for {BMS} Version 0.3.0},
  date         = {2011-05-05},
  howpublished = {R package vignette},
  url          = {https://cran.r-project.org/web/packages/BMS/vignettes/bms.pdf},
  urldate      = {2017-05-13},
  timestamp    = {2017-05-14},
}

@Article{Sala-I-Martin1997a,
  author       = {Sala-I-Martin, Xavier X.},
  title        = {I just ran two million regressions},
  journaltitle = {The American Economic Review},
  date         = {1997},
  volume       = {87},
  number       = {2},
  pages        = {178--183},
  url          = {http://www.jstor.org/stable/2950909},
  publisher    = {American Economic Association},
  timestamp    = {2017-05-14},
}

@Article{MakalicSchmidt2016a,
  author      = {Makalic, Enes and Schmidt, Daniel F.},
  title       = {High-Dimensional {Bayesian} lregularised regression with the {BayesReg} package},
  date        = {2016-11-21},
  eprint      = {1611.06649v3},
  eprintclass = {stat.CO},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1611.06649v3:PDF},
  keywords    = {stat.CO},
  timestamp   = {2017-05-15},
}

@Article{LeySteel2009a,
  author       = {Ley, Eduardo and Steel, Mark F. J.},
  title        = {On the effect of prior assumptions in {Bayesian} model averaging with applications to growth regression},
  journaltitle = {Journal of Applied Econometrics},
  date         = {2009-03},
  volume       = {24},
  number       = {4},
  pages        = {651--674},
  doi          = {10.1002/jae.1057},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Leamer1983a,
  author       = {Leamer, Edward E.},
  title        = {Let’s take the con out of econometrics},
  journaltitle = {The American Economic Review},
  date         = {1983},
  volume       = {73},
  number       = {1},
  pages        = {31--43},
  url          = {http://www.jstor.org/stable/1803924},
  publisher    = {American Economic Association},
  timestamp    = {2017-05-14},
}

@Article{IshwaranKogalurRao2010a,
  author       = {Ishwaran, Hemant and Kogalur, Udaya B. and Rao, J. Sunil},
  title        = {{spikeslab}: prediction and variable selection using spike and slab regression},
  journaltitle = {R Journal},
  date         = {2010},
  url          = {https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Ishwaran~et~al.pdf},
  urldate      = {2017-05-14},
  timestamp    = {2017-05-15},
}

@Article{HegreSambanis2006a,
  author       = {Hegre, Håvard and Sambanis, Nicholas},
  title        = {Sensitivity analysis of empirical results on civil war onset},
  journaltitle = {Journal of Conflict Resolution},
  date         = {2006-08},
  volume       = {50},
  number       = {4},
  pages        = {508--535},
  doi          = {10.1177/0022002706289303},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-14},
}

@Article{HahnCarvalho2015a,
  author       = {Hahn, P. Richard and Carvalho, Carlos M.},
  title        = {Decoupling shrinkage and selection in {Bayesian} linear models: a posterior summary perspective},
  journaltitle = {Journal of the American Statistical Association},
  date         = {2015-01},
  volume       = {110},
  number       = {509},
  pages        = {435--448},
  doi          = {10.1080/01621459.2014.993077},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-14},
}

@Article{Goenner2004a,
  author       = {Goenner, Cullen F.},
  title        = {Uncertainty of the {Liberal} {Peace}},
  journaltitle = {Journal of Peace Research},
  date         = {2004},
  volume       = {41},
  number       = {5},
  pages        = {589--605},
  url          = {http://www.jstor.org/stable/4149615},
  publisher    = {Sage Publications, Ltd.},
  timestamp    = {2017-05-21},
}

@Article{GelmanHillYajima2012a,
  author       = {Gelman, Andrew and Hill, Jennifer and Yajima, Masanao},
  title        = {Why we (Usually) don’t have to worry about multiple comparisons},
  journaltitle = {Journal of Research on Educational Effectiveness},
  date         = {2012-04},
  volume       = {5},
  number       = {2},
  pages        = {189--211},
  doi          = {10.1080/19345747.2011.618213},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-14},
}

@Article{FernandezLeySteel2001a,
  author       = {Fernández, Carmen and Ley, Eduardo and Steel, Mark F. J.},
  title        = {Benchmark priors for {Bayesian} model averaging},
  journaltitle = {Journal of Econometrics},
  date         = {2001-02},
  volume       = {100},
  number       = {2},
  pages        = {381--427},
  doi          = {10.1016/s0304-4076(00)00076-2},
  publisher    = {Elsevier {BV}},
  timestamp    = {2017-05-14},
}

@Article{EicherPapageorgiouRaftery2009a,
  author       = {Eicher, Theo S. and Papageorgiou, Chris and Raftery, Adrian E.},
  title        = {Default priors and predictive performance in {Bayesian} model averaging, with application to growth determinants},
  journaltitle = {Journal of Applied Econometrics},
  date         = {2009-08},
  volume       = {26},
  number       = {1},
  pages        = {30--55},
  doi          = {10.1002/jae.1112},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Unpublished{Clyde2017a,
  author       = {Clyde, Merlise A.},
  title        = {Using the {Bayesian} Adaptive Sampling ({BAS}) Package for {Bayesian} Model Averaging},
  date         = {2017-03-30},
  howpublished = {R package vignette},
  url          = {https://cran.r-project.org/web/packages/BAS/vignettes/BAS-vignette.html},
  urldate      = {2017-05-14},
  timestamp    = {2017-05-14},
}

@Article{Box-SteffensmeierZorn2001a,
  author       = {Box-Steffensmeier, Janet M. and Zorn, Christopher J. W.},
  title        = {Duration models and proportional hazards in political science},
  journaltitle = {American Journal of Political Science},
  date         = {2001},
  volume       = {45},
  number       = {4},
  pages        = {972--988},
  url          = {http://www.jstor.org/stable/2669335},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-21},
}

@Article{Nagler1994a,
  author       = {Nagler, Jonathan},
  title        = {Scobit: an alternative estimator to logit and probit},
  journaltitle = {American Journal of Political Science},
  date         = {1994},
  volume       = {38},
  number       = {1},
  pages        = {230--255},
  url          = {http://www.jstor.org/stable/2111343},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-21},
}

@InCollection{Liu2005a,
  author    = {Liu, Chuanhai},
  title     = {Robit regression: a simple robust alternative to logistic and probit regression},
  booktitle = {Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives},
  date      = {2005-07},
  publisher = {John Wiley {\&} Sons, Ltd},
  pages     = {227--238},
  doi       = {10.1002/0470090456.ch21},
  timestamp = {2017-05-21},
}

@Article{FearonLaitin2003a,
  author       = {Fearon, James D. and Laitin, David D.},
  title        = {Ethnicity, insurgency, and civil war},
  journaltitle = {American Political Science Review},
  date         = {2003-02},
  volume       = {97},
  number       = {01},
  pages        = {75--90},
  doi          = {10.1017/s0003055403000534},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{Tibshirani1996a,
  author       = {Tibshirani, Robert},
  title        = {Regression shrinkage and selection via the {Lasso}},
  journaltitle = {Journal of the Royal Statistical Society. Series B (Methodological)},
  date         = {1996},
  volume       = {58},
  number       = {1},
  pages        = {267--288},
  url          = {http://www.jstor.org/stable/2346178},
  publisher    = {[Royal Statistical Society, Wiley]},
  timestamp    = {2017-05-21},
}

@Article{LewandowskiKurowickaJoe2009a,
  author       = {Lewandowski, Daniel and Kurowicka, Dorota and Joe, Harry},
  title        = {Generating random correlation matrices based on vines and extended onion method},
  journaltitle = {Journal of Multivariate Analysis},
  date         = {2009-10},
  volume       = {100},
  number       = {9},
  pages        = {1989--2001},
  doi          = {10.1016/j.jmva.2009.04.008},
  publisher    = {Elsevier {BV}},
  timestamp    = {2017-05-21},
}

@Article{LeonardHsu1992a,
  author       = {Leonard, Tom and Hsu, John S. J.},
  title        = {{Bayesian} Inference for a Covariance Matrix},
  journaltitle = {The Annals of Statistics},
  date         = {1992-12},
  volume       = {20},
  number       = {4},
  pages        = {1669--1696},
  doi          = {10.1214/aos/1176348885},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{BarnardMcCullochMeng2000a,
  author       = {Barnard, John and McCulloch, Robert and Meng, Xiao-Li},
  title        = {Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage},
  journaltitle = {Statistica Sinica},
  date         = {2000},
  volume       = {10},
  number       = {4},
  pages        = {1281--1311},
  url          = {http://www.jstor.org/stable/24306780},
  publisher    = {Institute of Statistical Science, Academia Sinica},
  timestamp    = {2017-05-21},
}

@Article{JensenMcShaneWyner2009a,
  author       = {Jensen, Shane T. and McShane, Blakeley B. and Wyner, Abraham J.},
  title        = {Hierarchical {Bayesian} modeling of hitting performance in baseball},
  journaltitle = {Bayesian Analysis},
  date         = {2009-12},
  volume       = {4},
  number       = {4},
  pages        = {631--652},
  doi          = {10.1214/09-ba424},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{BayarriBergerForteEtAl2012a,
  author    = {Bayarri, M. J. and Berger, J. O. and Forte, A. and García-Donato, G.},
  title     = {Criteria for {Bayesian} model choice with application to variable selection},
  journal   = {The Annals of Statistics},
  year      = {2012},
  volume    = {40},
  number    = {3},
  pages     = {1550--1577},
  issn      = {00905364},
  url       = {http://www.jstor.org/stable/41713685},
  abstract  = {In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most general and compelling of the various criteria that have been suggested, together with a new criterion. We then illustrate the potential of these criteria in determining objective model selection priors by considering their application to the problem of variable selection in normal linear models. This results in a new model selection objective prior with a number of compelling properties.},
  publisher = {Institute of Mathematical Statistics},
  timestamp = {2018.05.01},
}

@Article{SteenbergenJones2002a,
  author       = {Steenbergen, Marco R. and Jones, Bradford S.},
  title        = {Modeling multilevel data structures},
  journaltitle = {American Journal of Political Science},
  date         = {2002},
  volume       = {46},
  number       = {1},
  pages        = {218--237},
  url          = {http://www.jstor.org/stable/3088424},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-21},
}

@Article{Gilardi2010a,
  author       = {Gilardi, Fabrizio},
  title        = {Who learns from what in policy diffusion processes?},
  journaltitle = {American Journal of Political Science},
  date         = {2010},
  volume       = {54},
  number       = {3},
  pages        = {650--666},
  url          = {http://www.jstor.org/stable/27821944},
  publisher    = {[Midwest Political Science Association, Wiley]},
  timestamp    = {2017-05-21},
}

@Book{Bates2010a,
  author    = {Bates, Douglas M.},
  title     = {{lme4}: mixed-effects modeling with {R}},
  date      = {2010-02-17},
  url       = {http://lme4.r-forge.r-project.org/book/front.pdf},
  urldate   = {2017-05-18},
  timestamp = {2017.05.18},
}

@Article{BatesMaechlerBolkerEtAl2014a,
  author      = {Bates, Douglas and Mächler, Martin and Bolker, Ben and Walker, Steve},
  title       = {Fitting linear mixed-effects models using {lme4}},
  date        = {2014-06-23},
  eprint      = {1406.5823v1},
  eprintclass = {stat.CO},
  eprinttype  = {arXiv},
  file        = {online:http\://arxiv.org/pdf/1406.5823v1:PDF},
  keywords    = {stat.CO},
  timestamp   = {2017-05-21},
}

@Article{BeckKatz2007a,
  author       = {Beck, Nathaniel and Katz, Jonathan N.},
  title        = {Random coefficient models for time-series—cross-section data: {Monte} {Carlo} experiments},
  journaltitle = {Political Analysis},
  date         = {2007},
  volume       = {15},
  number       = {02},
  pages        = {182--195},
  doi          = {10.1093/pan/mpl001},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{GelmanKing1993a,
  author       = {Gelman, Andrew and King, Gary},
  title        = {Why are {American} presidential election campaign polls so variable when votes are so predictable?},
  journaltitle = {British Journal of Political Science},
  date         = {1993-10},
  volume       = {23},
  number       = {04},
  pages        = {409},
  doi          = {10.1017/s0007123400006682},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{BafumiGelman2006a,
  author       = {Bafumi, Joseph and Gelman, Andrew},
  title        = {Fitting multilevel models when predictors and group effects correlate},
  journaltitle = {{SSRN} Electronic Journal},
  date         = {2006},
  doi          = {10.2139/ssrn.1010095},
  publisher    = {Elsevier {BV}},
  timestamp    = {2017-05-21},
}

@Article{GelmanShorBafumiEtAl2007a,
  author       = {Gelman, Andrew and Shor, Boris and Bafumi, Joseph and Park, David},
  title        = {Rich state, poor state, red state, blue state: what’s the matter with {Connecticut}?},
  journaltitle = {Quarterly Journal of Political Science},
  date         = {2007-11},
  volume       = {2},
  number       = {4},
  pages        = {345--367},
  doi          = {10.1561/100.00006026},
  publisher    = {Now Publishers},
  timestamp    = {2017-05-21},
}

@Book{RaudenbushBryk2001a,
  author    = {Raudenbush, Stephen W. and Bryk, Anthony S.},
  title     = {Hierarchical linear models: applications and data analysis methods},
  year      = {2001},
  date      = {2001-12-11},
  publisher = {SAGE PUBN},
  isbn      = {076191904X},
  pagetotal = {512},
  ean       = {9780761919049},
}

@Article{ORourkeSinnott2006a,
  author       = {O’Rourke, Kevin H. and Sinnott, Richard},
  title        = {The determinants of individual attitudes towards immigration},
  journaltitle = {European Journal of Political Economy},
  date         = {2006-12},
  volume       = {22},
  number       = {4},
  pages        = {838--861},
  doi          = {10.1016/j.ejpoleco.2005.10.005},
  publisher    = {Elsevier {BV}},
  timestamp    = {2018.05.01},
}

@Article{AndersenFetner2008a,
  author       = {Andersen, Robert and Fetner, Tina},
  title        = {Economic inequality and intolerance: attitudes toward homosexuality in 35 democracies},
  journaltitle = {American Journal of Political Science},
  date         = {2008-10},
  volume       = {52},
  number       = {4},
  pages        = {942--958},
  doi          = {10.1111/j.1540-5907.2008.00352.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Weldon2006a,
  author       = {Weldon, Steven A.},
  title        = {The Institutional Context of Tolerance for Ethnic Minorities: A Comparative, Multilevel Analysis of {Western Europe}},
  journaltitle = {American Journal of Political Science},
  date         = {2006-04},
  volume       = {50},
  number       = {2},
  pages        = {331--349},
  doi          = {10.1111/j.1540-5907.2006.00187.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Arzheimer2009a,
  author    = {Kai Arzheimer},
  title     = {Contextual factors and the extreme right vote in {Western Europe}, 1980-2002},
  journal   = {American Journal of Political Science},
  year      = {2009},
  volume    = {53},
  number    = {2},
  month     = apr,
  pages     = {259--275},
  doi       = {10.1111/j.1540-5907.2009.00369.x},
  publisher = {Wiley-Blackwell},
  timestamp = {2018.05.01},
}

@InCollection{Draper2008a,
  author    = {Draper, David},
  title     = {{Bayesian} multilevel analysis and {MCMC}},
  booktitle = {Handbook of Multilevel Analysis},
  date      = {2008},
  publisher = {Springer New York},
  pages     = {77--139},
  doi       = {10.1007/978-0-387-73186-5_2},
  timestamp = {2017-05-21},
}

@Article{HoogheReeskensStolleEtAl2009a,
  author       = {Hooghe, Marc and Reeskens, Tim and Stolle, Dietlind and Trappers, Ann},
  title        = {Ethnic diversity and generalized trust in {Europe}},
  journaltitle = {Comparative Political Studies},
  date         = {2009-02},
  volume       = {42},
  number       = {2},
  pages        = {198--223},
  doi          = {10.1177/0010414008325286},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-21},
}

@Article{HoogheMarks2004a,
  author       = {Hooghe, Liesbet and Marks, Gary},
  title        = {Does identity or economic rationality drive public opinion on {European} integration?},
  journaltitle = {PS: Political Science and Politics},
  date         = {2004},
  volume       = {37},
  number       = {3},
  pages        = {415--420},
  url          = {http://www.jstor.org/stable/4488854},
  publisher    = {[American Political Science Association, Cambridge University Press]},
  timestamp    = {2017-05-21},
}

@Article{AndersonSinger2008a,
  author       = {Anderson, C. J. and Singer, M. M.},
  title        = {The sensitive {Left} and the impervious {Right}: multilevel models and the politics of inequality, ideology, and legitimacy in {Europe}},
  journaltitle = {Comparative Political Studies},
  date         = {2008-04},
  volume       = {41},
  number       = {4-5},
  pages        = {564--599},
  doi          = {10.1177/0010414007313113},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-21},
}

@Article{MeerDethScheepers2009a,
  author       = {van der Meer, T. W. G. and van Deth, J. W. and Scheepers, P. L. H.},
  title        = {The politicized participant: ideology and political action in 20 democracies},
  journaltitle = {Comparative Political Studies},
  date         = {2009-02},
  volume       = {42},
  number       = {11},
  pages        = {1426--1457},
  doi          = {10.1177/0010414009332136},
  publisher    = {{SAGE} Publications},
  timestamp    = {2017-05-21},
}

@Article{IversenRosenbluth2006a,
  author       = {Iversen, Torben and Rosenbluth, Frances},
  title        = {The political economy of gender: explaining cross-national variation in the gender division of labor and the gender voting gap},
  journaltitle = {American Journal of Political Science},
  date         = {2006-01},
  volume       = {50},
  number       = {1},
  pages        = {1--19},
  doi          = {10.1111/j.1540-5907.2006.00166.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{LaxPhillips2009a,
  author       = {Lax, Jeffrey R. and Phillips, Justin H.},
  title        = {How should we estimate public opinion in {The States}?},
  journaltitle = {American Journal of Political Science},
  date         = {2009-01},
  volume       = {53},
  number       = {1},
  pages        = {107--121},
  doi          = {10.1111/j.1540-5907.2008.00360.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{Voeten2008a,
  author       = {Voeten, Erik},
  title        = {The impartiality of international judges: evidence from the {European Court of Human Rights}},
  journaltitle = {American Political Science Review},
  date         = {2008-11},
  volume       = {102},
  number       = {04},
  pages        = {417--433},
  doi          = {10.1017/s0003055408080398},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{FranchinoHoeyland2009a,
  author       = {Franchino, Fabio and Høyland, Bjørn},
  title        = {Legislative involvement in parliamentary systems: opportunities, conflict, and institutional constraints},
  journaltitle = {American Political Science Review},
  date         = {2009-10},
  volume       = {103},
  number       = {04},
  pages        = {607--621},
  doi          = {10.1017/s0003055409990177},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{DenisovaEllerFryeEtAl2009a,
  author       = {Denisova, Irina and Eller, Markus and Frye, Timothy and Zhuravskaya, Ekaterina},
  title        = {Who wants to revise privatization? the complementarity of market skills and institutions},
  journaltitle = {American Political Science Review},
  date         = {2009-05},
  volume       = {103},
  number       = {02},
  pages        = {284--304},
  doi          = {10.1017/s0003055409090248},
  publisher    = {Cambridge University Press ({CUP})},
  timestamp    = {2017-05-21},
}

@Article{AitkinLongford1986a,
  author       = {Aitkin, M. and Longford, N.},
  title        = {Statistical modelling issues in school effectiveness studies},
  journaltitle = {Journal of the Royal Statistical Society. Series A (General)},
  date         = {1986},
  volume       = {149},
  number       = {1},
  pages        = {1--43},
  url          = {http://www.jstor.org/stable/2981882},
  publisher    = {[Royal Statistical Society, Wiley]},
  timestamp    = {2017-05-21},
}

@Article{GoldsteinYangOmarEtAl2000a,
  author       = {Goldstein, Harvey and Yang, Min and Omar, Rumana and Turner, Rebecca and Thompson, Simon},
  title        = {Meta-analysis using multilevel models with an application to the study of class size effects},
  journaltitle = {Journal of the Royal Statistical Society: Series C (Applied Statistics)},
  date         = {2000-08},
  volume       = {49},
  number       = {3},
  pages        = {399--412},
  doi          = {10.1111/1467-9876.00200},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-05-21},
}

@Article{GoldsteinBrowneRasbash2002a,
  author       = {Goldstein, Harvey and Browne, William and Rasbash, Jon},
  title        = {Multilevel modelling of medical data},
  journaltitle = {Statistics in Medicine},
  date         = {2002},
  volume       = {21},
  number       = {21},
  pages        = {3291--3315},
  doi          = {10.1002/sim.1264},
  publisher    = {Wiley-Blackwell},
}

@Article{Jackman2000d,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Book{Goldstein2011a,
  author    = {Goldstein, H.},
  title     = {Multilevel statistical models},
  year      = {2011},
  date      = {2011-07-08},
  publisher = {John Wiley \& Sons},
  pagetotal = {382},
  ean       = {9781119956822},
}

@Book{SnijdersBosker2011a,
  author    = {Snijders, Tom A. B. and Bosker, Roel},
  title     = {Multilevel analysis},
  year      = {2011},
  date      = {2011-11-11},
  publisher = {Sage Publications Ltd.},
  isbn      = {184920201X},
  pagetotal = {368},
  ean       = {9781849202015},
}

@Book{Rabe-HeskethSkrondal2012a,
  author    = {Rabe-Hesketh, Sophia and Skrondal, Anders},
  title     = {Multilevel and longitudinal modeling using {Stata}, volumes {I} and {II}},
  date      = {2012},
  publisher = {Stata Press},
  isbn      = {978-1-59718-108-2},
  url       = {https://www.amazon.com/Multilevel-Longitudinal-Modeling-Using-Volumes-ebook/dp/B06XWHYLZT?SubscriptionId=0JYN1NVW651KCA56C102&tag=techkie-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=B06XWHYLZT},
}

@Book{Jiang2007a,
  author    = {Jiang, Jiming},
  title     = {Linear and generalized linear mixed models and their applications},
  year      = {2007},
  date      = {2007-05-30},
  publisher = {Springer New York},
  ean       = {9780387479460},
}

@Book{Jackman2009a,
  author    = {Jackman, Simon},
  title     = {{Bayesian} analysis for the social sciences},
  year      = {2009},
  date      = {2009-10-23},
  publisher = {John Wiley and Sons Ltd},
  isbn      = {0470011548},
  pagetotal = {598},
  ean       = {9780470011546},
  timestamp = {2017-05-21},
}

@Article{Linzer2013a,
  author    = {Drew A. Linzer},
  title     = {Dynamic bayesian forecasting of presidential elections in the {States}},
  journal   = {Journal of the American Statistical Association},
  year      = {2013},
  volume    = {108},
  number    = {501},
  month     = mar,
  pages     = {124--134},
  doi       = {10.1080/01621459.2012.737735},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.01},
}

@Article{Jackman2005a,
  author    = {Simon Jackman},
  title     = {Pooling the polls over an election campaign},
  journal   = {Australian Journal of Political Science},
  year      = {2005},
  volume    = {40},
  number    = {4},
  month     = dec,
  pages     = {499--517},
  doi       = {10.1080/10361140500302472},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.01},
}

@Article{Fariss2014a,
  author    = {Fariss, Christopher J.},
  title     = {Respect for Human Rights has Improved Over Time: Modeling the Changing Standard of Accountability},
  journal   = {American Political Science Review},
  year      = {2014},
  volume    = {108},
  number    = {02},
  month     = may,
  pages     = {297--318},
  doi       = {10.1017/s0003055414000070},
  publisher = {Cambridge University Press ({CUP})},
  timestamp = {2018.05.01},
}

@Article{SchnakenbergFariss2013a,
  author    = {Schnakenberg, Keith E. and Fariss, Christopher J.},
  title     = {Dynamic Patterns of Human Rights Practices},
  journal   = {Political Science Research and Methods},
  year      = {2013},
  volume    = {2},
  number    = {01},
  month     = oct,
  pages     = {1--31},
  doi       = {10.1017/psrm.2013.15},
  publisher = {Cambridge University Press ({CUP})},
  timestamp = {2018.05.01},
}

@Article{BaiWang2014a,
  author    = {Jushan Bai and Peng Wang},
  title     = {Identification and Bayesian Estimation of Dynamic Factor Models},
  journal   = {Journal of Business {\&} Economic Statistics},
  year      = {2014},
  volume    = {33},
  number    = {2},
  month     = jul,
  pages     = {221--240},
  doi       = {10.1080/07350015.2014.941467},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.01},
}

@Article{AguilarWest2000a,
  author    = {Omar Aguilar and Mike West},
  title     = {Bayesian Dynamic Factor Models and Portfolio Allocation},
  journal   = {Journal of Business {\&} Economic Statistics},
  year      = {2000},
  volume    = {18},
  number    = {3},
  month     = jul,
  pages     = {338--357},
  doi       = {10.1080/07350015.2000.10524875},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.01},
}

@Article{EroshevaCurtis2017c,
  author    = {Elena A. Erosheva and S. McKay Curtis},
  title     = {Dealing with Reflection Invariance in Bayesian Factor Analysis},
  journal   = {Psychometrika},
  year      = {2017},
  month     = mar,
  doi       = {10.1007/s11336-017-9564-y},
  publisher = {Springer Nature},
  timestamp = {2018.05.02},
}

@Article{Martin2003b,
  author    = {Andrew D. Martin},
  title     = {Bayesian Inference for Heterogeneous Event Counts},
  journal   = {Sociological Methods {\&} Research},
  year      = {2003},
  volume    = {32},
  number    = {1},
  month     = aug,
  pages     = {30--63},
  doi       = {10.1177/0049124103253500},
  publisher = {{SAGE} Publications},
  timestamp = {2018.05.02},
}

@Article{Curtis2010a,
  author    = {S. McKay Curtis},
  title     = {{BUGS} code for item response theory},
  journal   = {Journal of Statistical Software},
  year      = {2010},
  volume    = {36},
  number    = {Code Snippet 1},
  doi       = {10.18637/jss.v036.c01},
  publisher = {Foundation for Open Access Statistic},
}

@Article{LuoJiao2017b,
  author    = {Luo, Yong and Jiao, Hong},
  title     = {Using the {Stan} Program for {Bayesian} Item Response Theory},
  journal   = {Educational and Psychological Measurement},
  year      = {2017},
  month     = feb,
  pages     = {001316441769366},
  doi       = {10.1177/0013164417693666},
  publisher = {{SAGE} Publications},
  timestamp = {2018.05.02},
}

@Unpublished{GrantFurrCarpenterEtAl2015a,
  author    = {Grant, Robert L. and Furr, Daniel C. and Carpenter, Bob and Gelman, Andrew},
  title     = {Fitting {Bayesian} item response models in {Stata} and {Stan}},
  date      = {2015-01-12},
  url       = {http://www.stat.columbia.edu/~gelman/research/unpublished/stan_v_stata.pdf},
  urldate   = {2017-05-25},
  timestamp = {2017-05-25},
}

@Article{BayarriBergerForteEtAl2012b,
  author    = {Bayarri, M. J. and Berger, J. O. and Forte, A. and García-Donato, G.},
  title     = {Criteria for {Bayesian} model choice with application to variable selection},
  journal   = {The Annals of Statistics},
  year      = {2012},
  volume    = {40},
  number    = {3},
  pages     = {1550--1577},
  issn      = {00905364},
  url       = {http://www.jstor.org/stable/41713685},
  abstract  = {In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most general and compelling of the various criteria that have been suggested, together with a new criterion. We then illustrate the potential of these criteria in determining objective model selection priors by considering their application to the problem of variable selection in normal linear models. This results in a new model selection objective prior with a number of compelling properties.},
  publisher = {Institute of Mathematical Statistics},
  timestamp = {2018.05.02},
}

@Article{Curtis2010b,
  author    = {S. McKay Curtis},
  title     = {{BUGS} Code for item response theory},
  journal   = {Journal of Statistical Software},
  year      = {2010},
  volume    = {36},
  number    = {Code Snippet 1},
  doi       = {10.18637/jss.v036.c01},
  publisher = {Foundation for Open Access Statistic},
  timestamp = {2018.04.10},
}

@Article{Gelfand1998d,
  author    = {A. Gelfand},
  title     = {Model choice: a minimum posterior predictive loss approach},
  journal   = {Biometrika},
  year      = {1998},
  volume    = {85},
  number    = {1},
  month     = mar,
  pages     = {1--11},
  doi       = {10.1093/biomet/85.1.1},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018.05.02},
}

@Article{Jackman2000e,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{Jackman2000f,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{Jackman2001d,
  author    = {Simon Jackman},
  title     = {Multidimensional analysis of roll call data via {Bayesian} simulation: identification, estimation, inference, and model checking},
  journal   = {Political Analysis},
  year      = {2001},
  volume    = {9},
  number    = {3},
  pages     = {227--241},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791646},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{AlvarezGarrettLange1991b,
  author    = {R. Michael Alvarez and Geoffrey Garrett and Peter Lange},
  title     = {Government partisanship, labor organization, and macroeconomic performance},
  journal   = {The American Political Science Review},
  year      = {1991},
  volume    = {85},
  number    = {2},
  pages     = {539--556},
  issn      = {00030554},
  url       = {http://www.jstor.org/stable/1963174},
  publisher = {[American Political Science Association, Cambridge University Press]},
  timestamp = {2018.05.02},
}

@Article{Jackman2005d,
  author    = {Simon Jackman},
  title     = {Pooling the polls over an election campaign},
  journal   = {Australian Journal of Political Science},
  year      = {2005},
  volume    = {40},
  number    = {4},
  month     = dec,
  pages     = {499--517},
  doi       = {10.1080/10361140500302472},
  publisher = {Informa {UK} Limited},
  timestamp = {2018.05.02},
}

@Article{HanmerKalkan2012a,
  author       = {Hanmer, Michael J. and Kalkan, Kerem Ozan},
  title        = {Behind the curve: clarifying the best approach to calculating predicted probabilities and marginal effects from limited dependent variable models},
  journaltitle = {American Journal of Political Science},
  date         = {2012-07},
  volume       = {57},
  number       = {1},
  pages        = {263--277},
  doi          = {10.1111/j.1540-5907.2012.00602.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017-06-06},
}

@Article{Linzer2013b,
  author    = {Drew A. Linzer},
  title     = {Dynamic {Bayesian} forecasting of presidential elections in the {States}},
  journal   = {Journal of the American Statistical Association},
  year      = {2013},
  volume    = {108},
  number    = {501},
  pages     = {124--134},
  doi       = {10.1080/01621459.2012.737735},
  eprint    = {http://dx.doi.org/10.1080/01621459.2012.737735},
  timestamp = {2018.05.01},
}

@Article{Jackman2001e,
  author    = {Simon Jackman},
  title     = {Multidimensional analysis of roll call data via {Bayesian} simulation: identification, estimation, inference, and model checking},
  journal   = {Political Analysis},
  year      = {2001},
  volume    = {9},
  number    = {3},
  pages     = {227--241},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791646},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{Berger1984a,
  author    = {James O. Berger},
  title     = {Comment},
  journal   = {Journal of the American Statistical Association},
  year      = {1984},
  volume    = {79},
  number    = {386},
  pages     = {267--269},
  doi       = {10.1080/01621459.1984.10478039},
  eprint    = {https://doi.org/10.1080/01621459.1984.10478039},
  publisher = {Taylor \& Francis},
  timestamp = {2018.05.01},
}

@Article{Jackman2000g,
  author    = {Simon Jackman},
  title     = {Estimation and inference are missing data problems: unifying social science statistics via {Bayesian} simulation},
  journal   = {Political Analysis},
  year      = {2000},
  volume    = {8},
  number    = {4},
  pages     = {307--332},
  issn      = {10471987},
  url       = {http://www.jstor.org/stable/25791616},
  abstract  = {Bayesian simulation is increasingly exploited in the social sciences for estimation and inference of model parameters. But an especially useful (if often overlooked) feature of Bayesian simulation is that it can be used to estimate any function of model parameters, including "auxiliary" quantities such as goodness-of-fit statistics, predicted values, and residuals. Bayesian simulation treats these quantities as if they were missing data, sampling from their implied posterior densities. Exploiting this principle also lets researchers estimate models via Bayesian simulation where maximum-likelihood estimation would be intractable. Bayesian simulation thus provides a unified solution for quantitative social science. I elaborate these ideas in a variety of contexts: these include generalized linear models for binary responses using data on bill cosponsorship recently reanalyzed in Political Analysis, item—response models for the measurement of respondent's levels of political information in public opinion surveys, the estimation and analysis of legislators' ideal points from roll-call data, and outlier-resistant regression estimates of incumbency advantage in U.S. Congressional elections.},
  publisher = {[Oxford University Press, Society for Political Methodology]},
  timestamp = {2018.05.02},
}

@Article{Stigler2018b,
  author       = {Stigler, Stephen M.},
  title        = {{Richard} {Price}, the first {Bayesian}},
  journaltitle = {Statistical Science},
  year         = {2018},
  volume       = {33},
  number       = {1},
  month        = feb,
  pages        = {117--125},
  doi          = {10.1214/17-STS635},
  publisher    = {The Institute of Mathematical Statistics},
  timestamp    = {2018.05.02},
}

@Article{Stigler1983a,
  author    = {Stephen M. Stigler},
  title     = {Who discovered {Bayes's} theorem?},
  journal   = {The American Statistician},
  year      = {1983},
  volume    = {37},
  number    = {4},
  pages     = {290--296},
  url       = {http://www.jstor.org/stable/2682766},
  publisher = {[American Statistical Association, Taylor \& Francis, Ltd.]},
  timestamp = {2018.05.01},
}
{Fienberg2006a,
  author = "Fienberg, Stephen E.",
  doi = "10.1214/06-BA101",
  journaltitle = "Bayesian Analysis",
  month = "03",
  number = "1",
  pages = "1--40",
  publisher = "International Society for Bayesian Analysis",
  title = "When did {Bayesian} inference become \"{Bayesian}\"?",
  url = "https://doi.org/10.1214/06-BA101",
  volume = "1",
  year = "2006"
}

@Book{Lee2012a,
  author    = {Lee, Peter M.},
  title     = {{Bayesian} statistics: an introduction},
  year      = {2012},
  publisher = {Wiley},
  isbn      = {978-1118332573},
  editition = {4},
  timestamp = {2018.05.01},
}

@Book{Albert2009a,
  author    = {Albert, Jim},
  title     = {{Bayesian} computation with {R}},
  year      = {2009},
  series    = {Use R!},
  publisher = {Springer},
  isbn      = {978-0-387-92298-0},
  doi       = {10.1007/978-0-387-92298-0},
  timestamp = {2018.05.01},
}

@Article{Robert2016a,
  author       = {Robert, Christian P.},
  title        = {The expected demise of the {Bayes} factor},
  journaltitle = {Journal of Mathematical Psychology},
  year         = {2016},
  volume       = {72},
  month        = jun,
  pages        = {33--37},
  doi          = {10.1016/j.jmp.2015.08.002},
  timestamp    = {2018.05.01},
}

@Book{LunnJacksonBestEtAl2012a,
  author    = {David Lunn and Chris Jackson and Nicky Best and Andrew Thomas and David Spiegelhalter},
  title     = {The {BUGS} book: a practical introduction to {Bayesian} analysis},
  year      = {2012},
  series    = {Chapman \& Hall/CRC Texts in Statistical Science},
  publisher = {CRC Press},
  isbn      = {9781584888499},
  timestamp = {2018.05.01},
}

@Misc{wiki-conjugate-priors,
  author = {{Wikipedia contributors}},
  title  = {Conjugate prior --- {Wikipedia}{,} The Free Encyclopedia},
  year   = {2018},
  note   = {[Online; accessed 13-April-2018]},
  url    = {https://en.wikipedia.org/w/index.php?title=Conjugate_prior&oldid=835651973},
}

@Article{EroshevaCurtis2017d,
  author    = {Elena A. Erosheva and S. McKay Curtis},
  title     = {Dealing with Reflection Invariance in Bayesian Factor Analysis},
  journal   = {Psychometrika},
  year      = {2017},
  month     = mar,
  doi       = {10.1007/s11336-017-9564-y},
  publisher = {Springer Nature},
  timestamp = {2018.05.02},
}

@Article{LeemisMcQueston2008a,
  author    = {Lawrence M. Leemis and Jacquelyn T. McQueston},
  title     = {Univariate distribution relationships},
  journal   = {The American Statistician},
  year      = {2008},
  volume    = {62},
  number    = {1},
  pages     = {45--53},
  doi       = {10.1198/000313008X270448},
  eprint    = {https://doi.org/10.1198/000313008X270448},
  publisher = {Taylor \& Francis},
  timestamp = {2018.05.01},
}

@Book{ForbesEvansHastingsEtAl2010a,
  author    = {Forbes, Catherine and Evans, Merran and Hastings, Nicholas and Peacock, Brian},
  title     = {Statistical distributions},
  year      = {2010},
  edition   = {4},
  publisher = {Wiley},
  isbn      = {9780470390634},
  url       = {https://www.wiley.com/en-us/Statistical+Distributions%2C+4th+Edition-p-9781118097823},
  timestamp = {2018.05.01},
}

@Book{Asquith2011a,
  author   = {Asquith, William H.},
  title    = {Distributional analysis with {L}-moment statistics using the {R} environment for statistical computing},
  year     = {2011},
  isbn     = {978-1463508418},
  pulisher = {CreateSpace Independent Publishing Platform},
}

@Book{WimmerAltmann1999a,
  author    = {G. Wimmer and G. Altmann},
  title     = {Thesaurus of univariate discrete probability distributions},
  year      = {1999},
  publisher = {Stamm},
}

@Book{JohnsonKotzBalakrishnan1994a,
  author    = {Johnson, Norman L. and Kotz, Samuel and Balakrishnan, N.},
  title     = {Continuous univariate distributions, vol. 1},
  year      = {1994},
  edition   = {2},
  series    = {Wiley Series in Probability and Statistics},
  publisher = {Wiley-Interscience},
  isbn      = {978-0471584957},
}

@Book{JohnsonKotzBalakrishnan1995a,
  author    = {Johnson, Norman L. and Kotz, Samuel and Balakrishnan, N.},
  title     = {Continuous univariate distributions, vol. 2},
  year      = {1995},
  edition   = {2},
  series    = {Wiley Series in Probability and Statistics},
  publisher = {Wiley-Interscience},
  isbn      = {978-0471584940},
}

@Book{KotzBalakrishnanJohnson2000a,
  author    = {Kotz, Samuel and Balakrishnan, N. and Johnson, Norman L.},
  title     = {Continuous multivariate distributions, volume 1: models and applications},
  year      = {2000},
  edition   = {2},
  series    = {Wiley Series in Probability and Statistics},
  publisher = {Wiley-Interscience},
  isbn      = {978-0471183877},
}

@Book{JohnsonKotzBalakrishnan1997a,
  author    = {Johnson, Norman L. and Kotz, Samuel and Balakrishnan, N.},
  title     = {Discrete multivariate distributions},
  year      = {1997},
  edition   = {1},
  series    = {Wiley Series in Probability and Statistics},
  publisher = {Wiley-Interscience},
  isbn      = {978-0471128441},
}

@Article{BleiKucukelbirMcAuliffe2017a,
  author    = {David M. Blei and Alp Kucukelbir and Jon D. McAuliffe},
  title     = {Variational inference: a review for statisticians},
  journal   = {Journal of the American Statistical Association},
  year      = {2017},
  volume    = {112},
  number    = {518},
  pages     = {859--877},
  doi       = {10.1080/01621459.2017.1285773},
  eprint    = {https://doi.org/10.1080/01621459.2017.1285773},
  timestamp = {2018.05.01},
}

@Article{SmithGelfand1992b,
  author    = {A. F. M. Smith and A. E. Gelfand},
  title     = {{Bayesian} statistics without tears: a sampling-resampling perspective},
  journal   = {The American Statistician},
  year      = {1992},
  volume    = {46},
  number    = {2},
  pages     = {84--88},
  url       = {http://www.jstor.org/stable/2684170},
  publisher = {[American Statistical Association, Taylor \& Francis, Ltd.]},
  timestamp = {2018.05.01},
}

@Article{VehtariGelmanGabry2015a,
  author        = {Vehtari, Aki and Gelman, Andrew and Gabry, Jonah},
  title         = {{{Pareto} smoothed importance sampling}},
  journal       = {ArXiv e-prints},
  year          = {2015},
  month         = jul,
  eprint        = {1507.02646},
  url           = {https://arxiv.org/abs/1507.02646},
  archiveprefix = {arXiv},
  keywords      = {Statistics - Computation, Statistics - Methodology},
  primaryclass  = {stat.CO},
  timestamp     = {2018.05.01},
}

@Book{Stigler1999a,
  author    = {Stigler, Stephen M.},
  title     = {Statistics on the table: the history of statistical concepts and methods},
  year      = {1999},
  publisher = {Harvard UP},
  isbn      = {978-0674009790},
}

@InBook{Gelfand1995a,
  author  = {Gelfand, Alan E.},
  title   = {Model determination using sampling-based methods},
  year    = {1995},
  isbn    = {9780412055515},
  book    = {{Markov} chain {Monte} {Carlo} in practice},
  editors = {Gilks, W. R. and Richardson, S. and Spiegelhalter, David},
}

@Book{Ntzoufras2009a,
  author    = {Ntzoufras, Ioannis},
  title     = {{Bayesian} modeling using {WinBUGS}},
  year      = {2009},
  series    = {Wiley Series in Computational Statitistics},
  publisher = {Wiley},
  isbn      = {9780470434567},
  doi       = {10.1002/9780470434567},
}

@Article{BayarriBergerForteEtAl2012c,
  author    = {Bayarri, M. J. and Berger, J. O. and Forte, A. and García-Donato, G.},
  title     = {Criteria for {Bayesian} model choice with application to variable selection},
  journal   = {The Annals of Statistics},
  year      = {2012},
  volume    = {40},
  number    = {3},
  pages     = {1550--1577},
  issn      = {00905364},
  url       = {http://www.jstor.org/stable/41713685},
  abstract  = {In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to propose differing prior choices. We first formalize the most general and compelling of the various criteria that have been suggested, together with a new criterion. We then illustrate the potential of these criteria in determining objective model selection priors by considering their application to the problem of variable selection in normal linear models. This results in a new model selection objective prior with a number of compelling properties.},
  publisher = {Institute of Mathematical Statistics},
  timestamp = {2018.05.02},
}

@Article{Gelfand1998e,
  author    = {A. Gelfand},
  title     = {Model choice: a minimum posterior predictive loss approach},
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  number    = {1},
  month     = mar,
  pages     = {1--11},
  doi       = {10.1093/biomet/85.1.1},
  publisher = {Oxford University Press ({OUP})},
  timestamp = {2018.05.02},
}

@Article{AlbertAnderson1984b,
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  title     = {On the existence of maximum likelihood estimates in logistic regression models},
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  volume    = {71},
  number    = {1},
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  doi       = {10.1093/biomet/71.1.1},
  eprint    = {/oup/backfile/content_public/journal/biomet/71/1/10.1093/biomet/71.1.1/2/71-1-1.pdf},
  timestamp = {2018.05.02},
}

@Article{Geweke1993a,
  author    = {Geweke, J.},
  title     = {{Bayesian} treatment of the independent {Student-t} linear model},
  journal   = {Journal of Applied Econometrics},
  year      = {1993},
  volume    = {8},
  issn      = {08837252},
  url       = {http://www.jstor.org/stable/2285073},
  publisher = {Wiley},
  timestamp = {2018.05.01},
}

@Url{Stan-prior-choices,
  title = {{Stan} prior choice recommendations},
  url   = {https://github.com/stan-dev/stan/wiki/Prior-Choice-Recommendations},
}

@Article{GabrySimpsonVehtariEtAl2017a,
  author      = {Gabry, Jonah and Simpson, Daniel and Vehtari, Aki and Betancourt, Michael and Gelman, Andrew},
  title       = {Visualization in {Bayesian} workflow},
  date        = {2017-09-05},
  eprint      = {1709.01449v4},
  eprintclass = {stat.ME},
  eprinttype  = {arXiv},
  url         = {https://arxiv.org/abs/1709.01449},
  abstract    = {Bayesian data analysis is about more than just computing a posterior distribu- tion, and Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian data analysis, like all data analysis, is an iterative process of model building, inference, model checking and evaluation, and model expansion. Visualization is helpful in each of these stages of the Bayesian workflow and it is indispensable when drawing inferences from the types of modern, high-dimensional models that are used by applied researchers.},
  file        = {online:http\://arxiv.org/pdf/1709.01449v4:PDF},
  keywords    = {stat.ME, stat.AP},
  timestamp   = {2018.05.01},
}

@Misc{Fink1997a,
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  title  = {A Compendium of Conjugate Priors},
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}

@Article{ChungRabe-HeskethDorieEtAl2013a,
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@Book{Fox2016a,
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  isbn      = {978-1452205663},
  timestamp = {2017-04-25},
}

@Article{Gelman2007a,
  author       = {Gelman, Andrew},
  title        = {A {Bayesian} formulation of exploratory data analysis and goodness-of-fit testinga},
  journaltitle = {International Statistical Review},
  date         = {2007-01},
  volume       = {71},
  number       = {2},
  pages        = {369--382},
  doi          = {10.1111/j.1751-5823.2003.tb00203.x},
  publisher    = {Wiley-Blackwell},
  timestamp    = {2017.03.22},
}

@Book{Congdon2014a,
  author    = {Congdon, Peter},
  title     = {Applied {Bayesian} modelling},
  year      = {2014},
  edition   = {2},
  series    = {Wiley Series in Probability and Statistics},
  publisher = {Wiley},
  isbn      = {978-1-119-95151-3},
}

@Article{Heinze2006a,
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  title        = {A comparative investigation of methods for logistic regressionwith separated or nearly separated data},
  journaltitle = {Statistics in Medicine},
  year         = {2006},
  doi          = {10.1002/sim.2687},
}

@Article{HeinzeSchemper2002a,
  author       = {Heinze, Georg and Schemper, Michael},
  title        = {A solution to the problem of separation in logistic regression},
  journaltitle = {Statistics in Medicine},
  year         = {2002},
  doi          = {10.1002/sim.1047},
  url          = {https://doi.org/10.1002/sim.1047},
}

@Article{GelmanJakulinPittauEtAl2008a,
  author       = {Gelman, Andrew and Jakulin, Aleks and Pittau, Maria Grazia and Su, Yu-Sung},
  title        = {A weakly informative default prior distribution for logistic and other regression models},
  journaltitle = {The Annals of Applied Statistics},
  date         = {2008-12},
  volume       = {2},
  number       = {4},
  pages        = {1360--1383},
  doi          = {10.1214/08-aoas191},
  publisher    = {Institute of Mathematical Statistics},
}

@Article{Grimmer2011a,
  author       = {Grimmer, Justin},
  title        = {An introduction to {Bayesian} inference via variational approximations},
  journaltitle = {Political Analysis},
  date         = {2011},
  volume       = {19},
  number       = {01},
  pages        = {32--47},
  doi          = {10.1093/pan/mpq027},
  publisher    = {Cambridge University Press (CUP)},
  timestamp    = {2017-05-21},
}

@Article{KucukelbirEtAl2015a,
  author        = {Kucukelbir, A. and Ranganath, R. and Gelman, A. and Blei, David M.},
  title         = {Automatic variational inference in {Stan}},
  journal       = {ArXiv e-prints},
  year          = {2015},
  month         = jun,
  eprint        = {1506.03431},
  url           = {https://arxiv.org/abs/1506.03431},
  archiveprefix = {arXiv},
  keywords      = {Statistics - Machine Learning},
  primaryclass  = {stat.ML},
}

@InCollection{Duncan1961a,
  author    = {Duncan, O. D.},
  title     = {A socioeconomic index for all occupations},
  booktitle = {Occupations and Social Status},
  date      = {1961},
  editor    = {Reiss, A. J., Jr.},
  publisher = {Frre Press},
  timestamp = {2017-04-25},
}

@Book{Hoff2009a,
  author    = {Hoff, Peter D.},
  title     = {A first course in {Bayesian} statistical methods},
  year      = {2009},
  date      = {2009-06-11},
  series    = {Springer Texts in Statistics},
  publisher = {Springer-Verlag GmbH},
  isbn      = {0387922997},
  doi       = {10.1007/978-0-387-92407-6},
  ean       = {9780387922997},
}

@Article{WechslerIzbickiEsteves2013a,
  author       = {Wechsler, Sergio and Izbicki, Rafael and Esteves, Luìs Gustavo},
  title        = {A {Bayesian} look at nonidentifiability: a simple example},
  journaltitle = {The American Statistician},
  date         = {2013-05},
  volume       = {67},
  number       = {2},
  pages        = {90--93},
  doi          = {10.1080/00031305.2013.778787},
  publisher    = {Informa UK Limited},
  timestamp    = {2017-05-14},
}

@Article{ScottBerger2010a,
  author       = {Scott, James G. and Berger, James O.},
  title        = {{Bayes} and empirical-{Bayes} multiplicity adjustment in the variable-selection problem},
  journaltitle = {The Annals of Statistics},
  date         = {2010-10},
  volume       = {38},
  number       = {5},
  pages        = {2587--2619},
  doi          = {10.1214/10-Aos792},
  publisher    = {Institute of Mathematical Statistics},
  timestamp    = {2017-05-21},
}

@Article{Fienberg2006a,
  author       = {Fienberg, Stephen E.},
  title        = {When did {Bayesian} inference become "{Bayesian}"?},
  journaltitle = {Bayesian Analysis},
  year         = {2006},
  volume       = {1},
  number       = {1},
  month        = {3},
  pages        = {1--40},
  doi          = {10.1214/06-BA101},
  url          = {https://doi.org/10.1214/06-BA101},
  publisher    = {International Society for Bayesian Analysis},
}

@Article{Geweke1993,
  author    = {J. Geweke},
  title     = {{Bayesian} treatment of the independent {Student-t} linear model},
  journal   = {Journal of Applied Econometrics},
  year      = {1993},
  volume    = {8},
  pages     = {S19--S40},
  issn      = {08837252, 10991255},
  url       = {http://www.jstor.org/stable/2285073},
  publisher = {Wiley},
}

@Article{Zorn2005a,
  author       = {Zorn, Christopher},
  title        = {A Solution to separation in binary response models},
  journaltitle = {Political Analysis},
  date         = {2005},
  volume       = {13},
  number       = {2},
  pages        = {157--170},
  doi          = {10.1093/pan/mpi009},
  url          = {http://www.jstor.org/stable/25791803},
  publisher    = {[Oxford University Press, Society for Political Methodology]},
  timestamp    = {2017-05-04},
}

@Article{YuZhang2005a,
  author       = {Yu, Keming and Zhang, Jin},
  title        = {A three-parameter asymmetric {Laplace} distribution and its extension},
  journaltitle = {Communications in Statistics - Theory and Methods},
  date         = {2005-10},
  volume       = {34},
  number       = {9-10},
  pages        = {1867--1879},
  doi          = {10.1080/03610920500199018},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-04},
}

@Article{GoldsteinRasbashYangEtAl1993a,
  author       = {Goldstein, Harvey and Rasbash, Jon and Yang, Min and Woodhouse, Geoffrey and Pan, Huiqi and Nuttall, Desmond and Thomas, Sally},
  title        = {A multilevel analysis of school examination results},
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  date         = {1993-01},
  volume       = {19},
  number       = {4},
  pages        = {425--433},
  doi          = {10.1080/0305498930190401},
  publisher    = {Informa {UK} Limited},
  timestamp    = {2017-05-21},
}

@Article{DattaGhosh2013a,
  author    = {Datta, Jyotishka and Ghosh, Jayanta. K.},
  title     = {Asymptotic properties of {Bayes} risk for the horseshoe prior},
  journal   = {Bayesian Analysis},
  year      = {2013},
  volume    = {8},
  number    = {1},
  month     = {03},
  pages     = {111--132},
  doi       = {10.1214/13-BA805},
  url       = {https://dx.doi.org/10.1214/13-BA805},
  publisher = {International Society for Bayesian Analysis},
}

@Article{PiironenVehtari2017a,
  author    = {Piironen, Juho and Vehtari, Aki},
  title     = {Sparsity information and regularization in the horseshoe and other shrinkage priors},
  journal   = {Electron. J. Statist.},
  year      = {2017},
  volume    = {11},
  number    = {2},
  pages     = {5018--5051},
  doi       = {10.1214/17-EJS1337SI},
  url       = {https://doi.org/10.1214/17-EJS1337SI},
  fjournal  = {Electronic Journal of Statistics},
  publisher = {The Institute of Mathematical Statistics and the Bernoulli Society},
  timestamp = {2018.05.14},
}

@Comment{jabref-meta: databaseType:biblatex;}