Releases: easystats/effectsize
Releases · easystats/effectsize
CRAN release 0.4.5
effectsize 0.4.5
New features
eta_squared()
family now indicate the type of sum-of-squares used.rank_biserial()
estimates CIs using the normal approximation (previously used bootstrapping).hedges_g()
now used exact bias correction (thanks to @mdelacre for the suggestion!)glass_delta()
now estimates CIs using the NCP method based on Algina et al (2006).
Bug fixes
eta_squared()
family returns correctly returns the type 2/3 effect sizes for mixed ANOVAs fit withafex
.cohens_d()
family now correctly deals with missing factor levels ( #318 )cohens_d()
/hedges_g()
minor fix for CI with unequal variances.
Changes
mad_pooled()
(the robust version ofsd_pooled()
) now correctly pools the the two samples.
CRAN release 0.4.4-1
New features
standardize_parameters()
+eta_sqaured()
supporttidymodels
(when that the underlying model is supported; #311 ).cohens_d()
family now supportsPairs()
objects as input.standardize_parameters()
gains theinclude_response
argument (default toTRUE
) ( #309 ).
Bug fixes
kendalls_w()
now actually returns correct effect size. Previous estimates were incorrect, and based on transposing the groups and blocks.
CRAN release 0.4.4
effectsize
now supports R >= 3.4
.
New features
standardize_parameters()
now supports bootstrapped estimates (fromparameters::bootstrap_model()
andparameters::bootstrap_parameters()
).unstandardize()
which will reverse the effects ofstandardize()
.interpret_kendalls_w()
to interpret Kendall's coefficient of concordance.eta_squared()
family of functions can now also return effect sizes for the intercept by settinginclude_intercept = TRUE
( #156 ).
Bug fixes
standardize()
can now deal with dates ( #300 ).
CRAN release 0.4.3
Breaking Changes
oddsratio()
andriskratio()
- order of groups has been changed (the first groups is now the treatment group, and the second group is the control group), so that effect sizes are given as treatment over control (treatment / control) (previously was reversed). This is done to be consistent with other functions in R and ineffectsize
.
New features
cohens_h()
effect size for comparing two independent proportions.rank_biserial()
,cliffs_delta()
,rank_epsilon_squared()
andkendalls_w()
functions for effect sizes for rank-based tests.adjust()
gainskeep_intercept
argument to keep the intercept.eta_squared()
family of functions supportsAnova.mlm
objects (from thecar
package).effectsize()
:- supports Cohen's g for McNemar's test.
- Extracts OR from Fisher's Exact Test in the 2x2 case.
eta2_to_f2()
/f2_to_eta2()
to convert between two types of effect sizes for ANOVA ( #240 ).cohens_d()
family of functions gainmu
argument.
Bug fixes
adjust()
properly works whenmultilevel = TRUE
.cohens_d()
family /sd_pooled()
now properly fails when given a missing column name.
Changes
effectsize()
forhtest
objects now tries first to extract the data used for testing, and computed the effect size directly on that data.cohens_d()
family /sd_pooled()
now respect any transformations (e.g.I(log(x) - 3) ~ factor(y)
) in a passed formula.eta_squared()
family of functions gains averbose
argument.verbose
argument more strictly respected.glass_delta()
returns CIs based on the bootstrap.
0.4.1.2 (JOSS Paper)
version bump for JOSS
0.4.1 on CRAN
effectsize 0.4.1
Breaking Changes
cohens_d()
andglass_delta()
: Thecorrection
argument has been deprecated, in favor of it being correctly implemented inhedges_g()
( #222 ).eta_squared_posterior()
no longer usescar::Anova()
by default.
New features
effectsize()
gainstype =
argument for specifying which effect size to return.eta_squared_posterior()
can return a generalized Eta squared.oddsratio()
andriskratio()
functions for 2-by-2 contingency tables.standardize()
gains support formediation::mediate()
models.eta_squared()
family available formanova
objects.
Changes
eta_squared()
family of functions returns non-partial effect size for one-way between subjects design (#180).
Bug fixes
hedges_g()
correctly implements the available bias correction methods ( #222 ).- Fixed width of CI for Cohen's d and Hedges' g when using non-pooled SD.
CRAN release 0.4.0
Breaking Changes
standardize_parameters()
for multi-component models (such as zero-inflated) now returns the unstandardized parameters in some cases where standardization is not possible (previously returnedNA
s).- Column name changes:
eta_squared()
/F_to_eta2
families of function now has theEta2
format, where previously wasEta_Sq
.cramers_v
is nowCramers_v
New features
effectsize()
added support forBayesFactor
objects (Cohen's d, Cramer's v, and r).cohens_g()
effect size for paired contingency tables.- Generalized Eta Squared now available via
eta_squared(generalized = ...)
. eta_squared()
,omega_squared()
andepsilon_squared()
fully supportaovlist
,afex_aov
andmlm
(ormaov
) objects.standardize_parameters()
can now return Odds ratios / IRRs (or any exponentiated parameter) by settingexponentiate = TRUE
.- Added
cohens_f_squared()
andF_to_f2()
for Cohen's f-squared. cohens_f()
/cohens_f_squared()
can be used to estimate Cohen's f for the R-squared change between two models.standardize()
andstandardize_info()
work with weighted models / data ( #82 ).- Added
hardlyworking
(simulated) dataset, for use in examples. interpret_*
( #131 ):interpret_omega_squared()
added"cohen1992"
rule.interpret_p()
added Redefine statistical significance rules.
oddsratio_to_riskratio()
for converting OR to RR.
Changes
- CIs for Omega-/Epsilon-squared and Adjusted Phi/Cramer's V return 0s instead of negative values.
standardize()
for data frames gains theremove_na
argument for dealing withNA
s ( #147 ).standardize()
andstandardize_info()
now (and by extension,standardize_parameters()
) respect the weights in weighted models when standardizing ( #82 ).- Internal changes to
standardize_parameters()
(reducing co-dependency withparameters
) - argumentparameters
has been dropped.
Bug fixes
ranktransform(sign = TURE)
correctly (doesn't) deal with zeros.effectsize()
forhtest
works with Spearman and Kendall correlations ( #165 ).cramers_v()
andphi()
now work with goodness-of-fit data ( #158 )standardize_parameters()
for post-hoc correctly standardizes transformed outcome.- Setting
two_sd = TRUE
instandardize()
andstandardize_parameters()
(correctly) on uses 2-SDs of the predictors (and not the response). standardize_info()
/standardize_parameters(method = "posthoc")
work for zero-inflated models ( #135 )standardize_info(include_pseudo = TRUE)
/standardize_parameters(method = "pseudo")
are less sensitive in detecting between-group variation of within-group variables.interpret_oddsratio()
correctly treats extremely small odds the same as treats extremely large ones.
CRAN release 0.3.3
New features
standardize_parameters(method = "pseudo")
returns pseudo-standardized coefficients for (G)LMM models.d_to_common_language()
for common language measures of standardized differences (a-la Cohen's d).
Changes
r_to_odds()
family is now deprecated in favor ofr_to_oddsratio()
.interpret_odds()
is now deprecated in favor ofinterpret_oddsratio()
Bug fixes
CRAN release 0.3.2
New features
eta_squared_posterior()
for estimating Eta Squared for Bayesian models.eta_squared()
,omega_squared()
andepsilon_squared()
now works withols
/rms
models.
effectsize()
for classhtest
supportsoneway.test(...)
.
Bug fixes
- Fix minor miss-calculation of Chi-squared for 2*2 table with small samples ( #102 ).
- Fixed miss-calculation of signed rank in
ranktransform()
( #87 ). - Fixed bug in
standardize()
for standard objects with non-standard class-attributes (like vectors of classhaven_labelled
orvctrs_vctr
). - Fix
effectsize()
for one samplet.test(...)
( #95 ; thanks to pull request by @mutlusun )
CRAN release 0.3.1
New features
standardize_parameters()
now returns CIs ( #72 )eta_squared()
,omega_squared()
andepsilon_squared()
now works withgam
models.afex
models.lme
andanova.lme
objects.
- New function
equivalence_test()
for effect sizes. - New plotting methods in the
see
package.