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scale_ratio_2_analyze.R
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## Written by: Bryan Parthum; [email protected] ; May 2019
###################################################################################
########################## WILLINESS TO VOLUNTEER ##########################
###################################################################################
####################################################
##################################### PACKAGE SHOP
####################################################
# install.packages('mlogit')
# install.packages("viridis")
# install.packages("latex2exp")
# install.packages("tikzDevice")
####################################################
######## Check for and load Packages ###########
####################################################
## Clear worksace
rm(list = ls())
gc()
## This function will check if a package is installed, and if not, install it
pkgTest <- function(x) {
if (!require(x, character.only = T))
{
install.packages(x, dep = T)
if(!require(x, character.only = T)) stop("Package not found")
}
}
## These lines load the required packages
packages <- c("gmnl","mlogit","memisc","data.table","stargazer","plotly","readstata13",'ggpubr','Cairo','viridis','latex2exp','ggplot2','lmtest','haven') ## you can add more packages here
lapply(packages, pkgTest)
####################################################
########################################## PREAMBLE
####################################################
## Set working directory to location of this file
setwd("")
####################################################
####################### CHICAGO VS PORTLAND - MONEY
####################################################
## READ RESULTS
results <- readRDS("output/results_money.rds")
betas <- readRDS("output/betas_money.rds")
se <- readRDS("output/stderrors_money.rds")
## FIND OPTIMAL SCALE RATIO
maxLL <- max(results$LL, na.rm=T)
scale <- results[LL==maxLL,]$scale
scale
## STORE FOR LATER
money.scale <- scale
## READ IN FILE
cmo <- as.data.table(read.dta13("data/chicago_money.dta"))
pmo <- as.data.table(read.dta13("data/portland_money.dta"))
mo <- as.data.table(rbind(cmo,pmo))
## TRIM FAT
mo <- mo[, list(choice, fld_pctdec, hd_exc, pld_swm, money, c_id, id, chic_dum, alt)]
## TRANSFORM THINGS
mo[, fld_pctdec := as.numeric(fld_pctdec*100)]
mo[, money := as.numeric(money)]
## GEN ASC
mo[, asc := as.numeric(alt==3)]
mo[, asc_chi := asc*chic_dum]
mo[, fld_pctdec_chi := fld_pctdec*chic_dum]
mo[, hd_exc_chi := hd_exc*chic_dum]
mo[, pld_swm_chi := pld_swm*chic_dum]
mo[, money_chi := money*chic_dum]
## RESCALE OTHER DATA
mo2 <- as.data.table(mo)
mo2[chic_dum==0, asc := asc*scale]
mo2[chic_dum==0, fld_pctdec := fld_pctdec*scale]
mo2[chic_dum==0, hd_exc := hd_exc*scale]
mo2[chic_dum==0, pld_swm := pld_swm*scale ]
mo2[chic_dum==0, money := money*scale]
write_dta(mo2,'output/scaled_money.dta', version=14)
## ORDER
setkeyv(mo,c('chic_dum','id','c_id','alt'))
setkeyv(mo2,c('chic_dum','id','c_id','alt'))
## MLOGIT DATA
p <- mlogit.data(mo,
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='money')
ch <- mlogit.data(mo[chic_dum==1,],
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='money')
po <- mlogit.data(mo[chic_dum==0,],
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='money')
## MLOGIT DATA
scaled <- mlogit.data(mo2,
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='money')
## MODELS
chi <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=ch,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T)
chi <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=ch,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start=coef(chi))
por <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=po,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T)
por <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=po,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start=coef(por))
start <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=p,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T)
poo <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=p,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start = coef(start))
sca <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + money | 0 ,
data=scaled,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',money='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start = coef(poo))
saveRDS(chi,file="output/chicago_money_mixl.rds")
saveRDS(por,file="output/portland_money_mixl.rds")
saveRDS(poo,file="output/pooled_money_mixl.rds")
saveRDS(sca,file="output/scaled_money_mixl.rds")
####################################################
######################## CHICAGO VS PORTLAND - TIME
####################################################
## READ RESULTS
results <- readRDS("output/results_time.rds")
betas <- readRDS("output/betas_time.rds")
se <- readRDS("output/stderrors_time.rds")
## FIND OPTIMAL SCALE RATIO
maxLL <- max(results$LL, na.rm=T)
scale <- results[LL==maxLL,]$scale
scale
## STORE FOR LATER
time.scale <- scale
time.scale
## READ IN FILE
cti <- as.data.table(read.dta13("data/chicago_time.dta"))
pti <- as.data.table(read.dta13("data/portland_time.dta"))
ti <- as.data.table(rbind(cti,pti))
## TRIM FAT
ti <- ti[, list(choice, fld_pctdec, hd_exc, pld_swm, time, c_id, id, chic_dum, alt)]
## GEN ASC
ti[, asc := as.numeric(alt==3)]
## TRANSFORM THINGS
ti[, fld_pctdec := as.numeric(fld_pctdec*100)]
ti[, time := as.numeric(time)]
## RESCALE OTHER DATA
ti2 <- as.data.table(ti)
ti2[chic_dum==0, asc := asc*scale]
ti2[chic_dum==0, fld_pctdec := fld_pctdec*scale]
ti2[chic_dum==0, hd_exc := hd_exc*scale]
ti2[chic_dum==0, pld_swm := pld_swm*scale ]
ti2[chic_dum==0, time := time*scale]
write_dta(ti2,'output/scaled_time.dta', version=14)
## ORDER
setkeyv(ti,c('chic_dum','id','c_id','alt'))
setkeyv(ti2,c('chic_dum','id','c_id','alt'))
## MLOGIT DATA
p <- mlogit.data(ti,
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='time')
ch <- mlogit.data(ti[chic_dum==1,],
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='time')
po <- mlogit.data(ti[chic_dum==0,],
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='time')
## MLOGIT DATA
scaled <- mlogit.data(ti2,
id.var='id',
chid.var = 'c_id',
choice='choice',
shape='long',
alt.var='alt',
opposite='time')
## MODELS
chi <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + time | 0 ,
data=ch,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',time='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start=coef(chi))
por <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + time | 0 ,
data=po,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',time='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start=coef(por))
start <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + time | 0 ,
data=p,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',time='ln'),
R=500,
halton=NA,
panel=T,
correlation=T)
poo <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + time | 0 ,
data=p,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',time='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start = coef(start))
sca <- mlogit(choice ~ asc + fld_pctdec + hd_exc + pld_swm + time | 0 ,
data=scaled,
rpar=c(asc='n',fld_pctdec='n',hd_exc='n',pld_swm='n',time='ln'),
R=500,
halton=NA,
panel=T,
correlation=T,
start = coef(poo))
saveRDS(chi,file="output/chicago_time_mixl.rds")
saveRDS(por,file="output/portland_time_mixl.rds")
saveRDS(poo,file="output/pooled_time_mixl.rds")
saveRDS(sca,file="output/scaled_time_mixl.rds")
####################################################
################################### HYPOTHESIS TESTS
####################################################
############################
############### READ FILES
############################
## READ RESULTS
mo.results <- readRDS("output/results_money.rds")
mo.betas <- readRDS("output/betas_money.rds")
mo.se <- readRDS("output/stderrors_money.rds")
ti.results <- readRDS("output/results_time.rds")
ti.betas <- readRDS("output/betas_time.rds")
ti.se <- readRDS("output/stderrors_time.rds")
chi.mo <- readRDS("output/chicago_money_mixl.rds")
por.mo <- readRDS("output/portland_money_mixl.rds")
pooled.mo <- readRDS("output/pooled_money_mixl.rds")
scaled.mo <- readRDS("output/scaled_money_mixl.rds")
chi.ti <- readRDS("output/chicago_time_mixl.rds")
por.ti <- readRDS("output/portland_time_mixl.rds")
pooled.ti <- readRDS("output/pooled_time_mixl.rds")
scaled.ti <- readRDS("output/scaled_time_mixl.rds")
############################
############### MONEY TESTS
############################
## TESTS
chi.ll.money <- as.numeric(logLik(chi.mo))
por.ll.money <- as.numeric(logLik(por.mo))
poo.ll.money <- as.numeric(logLik(pooled.mo))
sca.ll.money <- as.numeric(logLik(scaled.mo))
## H_0: EQUAL PARAMETERS
test <- 2*((chi.ll.money + por.ll.money) - sca.ll.money)
crit <- qchisq(p = 0.95, df = 46)
money.equalB <- test > crit
money.pvalueB <- pchisq(test, 46,lower.tail=F)
money.testB <- test
## H_0: EQUAL SCALE
test <- 2*(sca.ll.money - poo.ll.money)
crit <- qchisq(p = 0.95, df = 1)
money.equalM <- test > crit
money.pvalueM <- pchisq(test, 1,lower.tail=F)
money.testM <- test
############################
############### TIME TESTS
############################
## TESTS
chi.ll.time <- as.numeric(logLik(chi.ti))
por.ll.time <- as.numeric(logLik(por.ti))
poo.ll.time <- as.numeric(logLik(pooled.ti))
sca.ll.time <- as.numeric(logLik(scaled.ti))
## H_0: EQUAL PARAMETERS
test <- 2*((chi.ll.time + por.ll.time) - sca.ll.time)
crit <- qchisq(p = 0.95, df = 46)
time.equalB <- test > crit
time.pvalueB <- pchisq(test, 46,lower.tail=F)
time.testB <- test
critB <- crit
## H_0: EQUAL SCALE
test <- 2*(sca.ll.time - poo.ll.time)
crit <- qchisq(p = 0.95, df = 1)
time.equalM <- test > crit
time.pvalueM <- pchisq(test, 1,lower.tail=F)
critM <- crit
time.testM <- test
############################
############### PRINT TESTS
############################
## LL - MONEY
chi.ll.money
por.ll.money
poo.ll.money
sca.ll.money
## LL - TIME
chi.ll.time
por.ll.time
poo.ll.time
sca.ll.time
## RELATIVE SCALE
money.scale
time.scale
## TEST STATISTICS
critB
critM
money.testB
money.testM
money.pvalueB
money.pvalueM
time.testB
time.testM
time.pvalueB
time.pvalueM
## HYPOTHESES
money.equalB
money.equalM
time.equalB
time.equalM
##########################################
########################### PLOT - MONEY
##########################################
## READ IN RESULTS
results <- as.data.table(readRDS("output/results_money.rds"))
results[, color := 'Ha',]
## CREATE SCALAR
maxLL <- max(results$LL, na.rm=T)
scalar <- results[LL==maxLL,]$scale
results[, scalar := scalar,]
## HORIZONTAL LINES
results[, testline := (chi.ll.money + por.ll.money),]
results[, testline_color := 'Chicago + Portland',]
results[, pooled := poo.ll.money - money.testM/2,]
results[, pooled_color := 'Pooled, Scale = 1',]
results[, scaled := sca.ll.money,]
results$testline
## TEST VALUES
crit1 <- qchisq(p = 0.95, df = 46)/2
crit1
## PLOT
money <- ggplot(results) +
geom_line(aes(x=scale, y=LL, linetype = "solid"), size=0.75) +
geom_vline(aes(xintercept=scalar),linetype = "solid", size=0.75) +
geom_vline(aes(xintercept=1),linetype = "dashed", size=0.75) +
geom_line(aes(x=scale, y=testline, linetype = "twodash"), size=0.75) +
geom_ribbon(aes(x=scale, ymin = LL - crit1, ymax = LL + crit1), fill = "grey70", color="grey70",alpha = 0.3,linetype = "dashed") +
scale_y_continuous(breaks = seq(-2000,-1500,100),
limits=c(-2000,-1550),
expand = c(0,0)) +
scale_x_continuous(breaks = seq(0,2.1,by=0.2),
expand = c(0,0)) +
scale_linetype_discrete(labels = unname(TeX(c("$LL_\\sigma$","$(LL_R + LL_U)$")))) +
annotate("text",x = .33, y = -1608,
label=TeX("$(LL_C + LL_P)= \ -1619.28$", output = "character"),
hjust=0, parse=T) +
annotate("text",x = 1.1, y = -1975,
label=TeX("$\\sigma =1.05$", output = "character"),
hjust=0, parse=T) +
labs(x="Relative Scale Factor",
y="Log-likelihood",
linetype="") +
theme_bw() +
theme(panel.grid.minor.y=element_blank(),
panel.grid.major.y=element_blank(),
panel.grid.minor.x=element_blank(),
panel.grid.major.x=element_blank(),
legend.position = 'bottom',
legend.text=element_text(size=16))
money
ggsave(money,filename="plots/scale_money.png",h=5,w=8,type="cairo-png")
##########################################
########################### PLOT - MONEY
##########################################
## READ IN RESULTS
results <- as.data.table(readRDS("output/results_time.rds"))
results[, color := 'Ha',]
## CREATE SCALAR
maxLL <- max(results$LL, na.rm=T)
scalar <- results[LL==maxLL,]$scale
results[, scalar := scalar,]
## HORIZONTAL LINES
results[, testline := (chi.ll.time + por.ll.time),]
results[, testline_color := 'Chicago + Portland',]
results[, pooled := poo.ll.time - time.testM/2,]
results[, pooled_color := 'Pooled, Scale = 1',]
results[, scaled := sca.ll.time,]
results$testline
## TEST VALUES
crit1 <- qchisq(p = 0.95, df = 46)/2
crit1
crit2 <- qchisq(p = 0.95, df = 1)/2
crit2
## PLOT
time <- ggplot(results) +
geom_line(aes(x=scale, y=LL, linetype = "solid"), size=0.75) +
geom_vline(aes(xintercept=scalar),linetype = "solid", size=0.75) +
geom_vline(aes(xintercept=1),linetype = "dashed", size=0.75) +
geom_line(aes(x=scale, y=testline, linetype = "twodash"), size=0.75) +
geom_ribbon(aes(x=scale, ymin = LL - crit1, ymax = LL + crit1), fill = "grey70", color="grey70",alpha = 0.3,linetype = "dashed") +
scale_linetype_discrete(labels = unname(TeX(c("$LL_\\sigma$","$(LL_R + LL_U)$")))) +
scale_y_continuous(breaks = seq(-2000,-1500,100),
limits=c(-2000,-1550),
expand = c(0,0)) +
scale_x_continuous(breaks = seq(0,2.1,by=0.2),
expand = c(0,0)) +
scale_color_viridis(discrete=T,alpha=0.6) +
annotate("text",x = .33, y = -1605,
label=TeX("$(LL_C + LL_P)= \ -1615.70$", output = "character"),
hjust=0, parse=T) +
annotate("text",x = 1.35, y = -1975,
label=TeX("$\\sigma =1.30$", output = "character"),
hjust=0, parse=T) +
labs(x="Relative Scale Factor",
y="Log-likelihood",
linetype="") +
theme_bw() +
theme(panel.grid.minor.y=element_blank(),
panel.grid.major.y=element_blank(),
panel.grid.minor.x=element_blank(),
panel.grid.major.x=element_blank(),
legend.position = 'bottom',
legend.text=element_text(size=16))
time
ggsave(time,filename="plots/scale_time.png",h=5,w=8,type="cairo-png")
## END OF SCRIPT. Have a nice day!