recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
mm_by_political_extremes$feature <- factor(mm_by_political_extremes$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
mm_by_political_extremes <- mm_by_political_extremes %>% filter(grepl("Sociotropic",feature))
mm_by_political_extremes$model <- mm_by_political_extremes$model %>%
recode("Ideological Extremists" = "Ideological \nExtremists")
mm_by_political_extremes$lower_84 <- mm_by_political_extremes$estimate-1.44*mm_by_political_extremes$std.error
mm_by_political_extremes$upper_84 <- mm_by_political_extremes$estimate+1.44*mm_by_political_extremes$std.error
mm_by_political_extremes$term <- mm_by_political_extremes$term %>%
recode("<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] support it" = "Yes",
" most [NATIONALITY] oppose it" = "No")
# This is Figure 3c)
mm_by_political_extremes %>%
ggplot(aes(xmin=lower,xmax=upper,y=term,x=estimate,color=model,shape=model))+
geom_point(size=1.75,position=position_dodge(width = 0.6))+
geom_errorbarh(height=0,size=0.75,position=position_dodge(width = 0.6))+
geom_errorbarh(height=0,
size=1.5,
data=mm_by_political_extremes,
aes(xmin=lower_84,xmax=upper_84,y=term),
position=position_dodge(width = 0.6))+
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
ggtitle("c) Long-term Utilitarian Calculus") +
scale_colour_grey(start = 0.25, end = .6) +
theme(plot.title = element_text(face="bold"),
axis.text=element_text(colour="black"),
axis.title=element_text(size=8,colour="black"),
strip.text.y = element_text(angle = 0, face="bold"),
#          strip.background =element_rect(fill="white"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
#panel.grid = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.position = "bottom",
legend.title = element_blank())
####################
# Replication code for Wratil, Wäckerle: "Majority Representation and Legitimacy: Survey-Experimental Evidence from the European Union" ####
# Appendix ####
# General Information: All plots in the paper and the Appendix are done using
# the tikzDevice package. This means that plots from this script displayed
# in the preview window or saved to pdf/png might look slightly different, but
# only in terms of size of axis labels, headings and the like. The quantities
# displayed are equivalent to the ones in the paper/appendix.
#### Intro ####
library(cregg)
library(tidyverse)
library(dotwhisker)
library(scales)
library(gridExtra)
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
load("datasets_eu.RData")
label_changes=c("<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] support it" = "Yes",
" most [NATIONALITY] oppose it" = "No")
label_changes_topics=c("<blank>" = "No",
"Most EU citizens support this decision, most [NATIONALITY] support it" = "EU support, national support",
"Most EU citizens oppose this decision, most [NATIONALITY] support it" = "EU oppose, national support",
"Most EU citizens support this decision, most [NATIONALITY] oppose it" = "EU support, national oppose",
"Most EU citizens oppose this decision, most [NATIONALITY] oppose it" = "EU oppose, national oppose")
theme_demos <- theme(plot.title = element_text(face="bold"),
axis.text=element_text(colour="black"),
axis.title=element_text(size=8),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.title = element_blank())
theme_voting <-   theme(plot.title = element_text(face="bold"),
axis.title=element_text(size=8),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.position = "bottom",
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1))
theme_results <-  theme(plot.title = element_text(face="bold"),
axis.text=element_text(colour="black"),
axis.title=element_text(size=8,colour="black"),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.position = "bottom",
legend.title = element_blank())
results_eu_main_amce <- cregg::amce(legitimate ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, data = eudata_long, id = ~UUID)
results_eu_main_amce$level=recode(results_eu_main_amce$level,
"<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] oppose it" = "No",
" most [NATIONALITY] support it" = "Yes")
results_eu_main_amce$feature=recode(results_eu_main_amce$feature,
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)",
"congruence" = "Egotropic representation")
results_eu_main_amce <- results_eu_main_amce[c(12,13,8,9,10,11,1,2,3,4,5,6,7),]
names(results_eu_main_amce) <- c("Outcome","statistic","Feature","Level","Estimate","Std.Error","z","p","Lower","Upper")
results_eu_main_amce_accept <- cregg::amce(accept ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, data = eudata_long, id = ~UUID)
results_eu_main_amce_accept$level=recode(results_eu_main_amce_accept$level,
"<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] oppose it" = "No",
" most [NATIONALITY] support it" = "Yes")
results_eu_main_amce_accept$feature=recode(results_eu_main_amce_accept$feature,
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)",
"congruence" = "Egotropic representation")
results_eu_main_amce_accept <- results_eu_main_amce_accept[c(12,13,8,9,10,11,1,2,3,4,5,6,7),]
#results_eu_main_amce_accept$feature <- factor(results_eu_main_amce_accept$feature, levels = c("Egotropic representation",
#                                                                                              "Sociotropic representation (EU-wide)",
#                                                                                              "Sociotropic representation (national)",
#                                                                                              "Consultation",
#                                                                                              "Voting in Council",
#                                                                                              "Voting in EP"))
names(results_eu_main_amce_accept) <- c("Outcome","statistic","Feature","Level","Estimate","Std.Error","z","p","Lower","Upper")
# This is Table J1
print(xtable::xtable(rbind(results_eu_main_amce %>%
select(-statistic),
results_eu_main_amce_accept %>%
select(-statistic)), file="amce_table.tex"),
include.rownames=FALSE)
R.version
library(cregg)
library(tidyverse)
library(dotwhisker)
sessionInfo()
load(file="pretest.RData")
View(pretest_scales_all)
load("datasets_eu.RData")
View(eudata_long)
####################
# Replication code for Wratil, Wäckerle: "Majority Representation and Legitimacy: Survey-Experimental Evidence from the European Union" ####
# Appendix ####
# General Information: All plots in the paper and the Appendix are done using
# the tikzDevice package. This means that plots from this script displayed
# in the preview window or saved to pdf/png might look slightly different, but
# only in terms of size of axis labels, headings and the like. The quantities
# displayed are equivalent to the ones in the paper/appendix.
#### Intro ####
library(cregg)
library(tidyverse)
library(dotwhisker)
library(scales)
library(gridExtra)
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
load("datasets_eu.RData")
View(eudata)
View(eudata_long)
View(eudata)
eudata <- eudata %>%
select(-starts_with("ideology"),-starts_with("leader"),-starts_with("mp"))
View(eudata)
View(eudata)
save(file="datasets_eu.RData",eudata,eudata_long)
####################
# Replication code for Wratil, Wäckerle: "Majority Representation and Legitimacy: Survey-Experimental Evidence from the European Union" ####
# General Information: All plots in the paper and the Appendix are done using
# the tikzDevice package. This means that plots from this script displayed
# in the preview window or saved to pdf/png might look slightly different, but
# only in terms of size of axis labels, headings and the like. The quantities
# displayed are equivalent to the ones in the paper/appendix.
#### Intro ####
library(cregg)
library(tidyverse)
library(dotwhisker)
library(tikzDevice)
options(tikzDocumentDeclaration = "\\documentclass[12pt]{article}")
sessionInfo()
load("datasets_eu.RData")
# There are two datasets in the RData file: "eudata", which is the original
# dataset with one observation per respondent and "eudata_long", which has
# one observation per answered vignette (each respondent answered 5 vignettes).
#### Figure 2a) ####
results_eu_main <- cregg::mm(legitimate ~
congruence+
consult +
council+
ep +
eu_opinion +
national_opinion, data = eudata_long, id = ~UUID)
names(results_eu_main)[4]="term"
results_eu_main$feature <- results_eu_main$feature %>%
recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
results_eu_main$feature <- factor(results_eu_main$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
results_eu_main$lower_84 <- results_eu_main$estimate-1.44*results_eu_main$std.error
results_eu_main$upper_84 <- results_eu_main$estimate+1.44*results_eu_main$std.error
results_eu_main$term <- results_eu_main$term %>%
recode("<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] support it" = "Yes",
" most [NATIONALITY] oppose it" = "No")
# This is Figure 2a)
results_eu_main %>%
ggplot(aes(xmin=lower,xmax=upper,y=term,x=estimate))+
geom_point(size=1.75)+
geom_errorbarh(height=0,size=0.75)+
geom_errorbarh(height=0,size=1.5,data=results_eu_main,aes(xmin=lower_84,xmax=upper_84,y=term))+
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
ggtitle("") +
scale_color_manual(values = c("black")) +
theme(plot.title = element_text(face="bold"),
legend.position = "none",
axis.text=element_text(colour="black"),
axis.title=element_text(size=8,colour="black"),
strip.text.y = element_text(angle = 0, face="bold"),
#          strip.background =element_rect(fill="white"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
#panel.grid = element_blank(),
panel.spacing.x = unit(0,"line"))
#### Figure I12 ####
mm_by_topicimpression_vignette1=cj(eudata_long %>% filter(vignette=="Vignette 1"), legitimate ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, id = ~UUID, by = ~topic_impression_rec_median, estimate = "mm")
names(mm_by_topicimpression_vignette1)[names(mm_by_topicimpression_vignette1)=="level"]="term"
names(mm_by_topicimpression_vignette1)[names(mm_by_topicimpression_vignette1)=="topic_impression_rec_median"]="model"
mm_by_topicimpression_vignette1$feature <- mm_by_topicimpression_vignette1$feature %>%
recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
mm_by_topicimpression_vignette1$feature <- factor(mm_by_topicimpression_vignette1$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
mm_by_topicimpression_vignette1 = mm_by_topicimpression_vignette1 %>% filter(grepl("Sociotropic",feature))
mech_2_vignette1 <- dwplot(mm_by_topicimpression_vignette1,dot_args = list(size = 2,aes(shape = model)),whisker_args = list(aes(linetype = model))) %>%
relabel_predictors(label_changes) +
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
expand_limits(x=c(4,4.6))+
ggtitle("Vignette 1") +
scale_colour_grey(start = 0.25, end = .6) +
theme_results
mm_by_topicimpression_vignette2_5=cj(eudata_long %>% filter(vignette%in%c("Vignette 2","Vignette 3",
"Vignette 4","Vignette 5")),
legitimate ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, id = ~UUID, by = ~topic_impression_rec_median, estimate = "mm")
names(mm_by_topicimpression_vignette2_5)[names(mm_by_topicimpression_vignette2_5)=="level"]="term"
names(mm_by_topicimpression_vignette2_5)[names(mm_by_topicimpression_vignette2_5)=="topic_impression_rec_median"]="model"
mm_by_topicimpression_vignette2_5$feature <- mm_by_topicimpression_vignette2_5$feature %>%
recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
mm_by_topicimpression_vignette2_5$feature <- factor(mm_by_topicimpression_vignette2_5$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
mm_by_topicimpression_vignette2_5 = mm_by_topicimpression_vignette2_5 %>% filter(grepl("Sociotropic",feature))
mech_2_vignette2_5 <- dwplot(mm_by_topicimpression_vignette2_5,dot_args = list(size = 2,aes(shape = model)),whisker_args = list(aes(linetype = model))) %>%
relabel_predictors(label_changes) +
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
expand_limits(x=c(4,4.6))+
ggtitle("Vignette 2,3,4 and 5") +
scale_colour_grey(start = 0.25, end = .6) +
theme_results
#### Intro ####
library(cregg)
library(tidyverse)
library(dotwhisker)
library(scales)
library(gridExtra)
get_legend<-function(myggplot){
tmp <- ggplot_gtable(ggplot_build(myggplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
load("datasets_eu.RData")
label_changes=c("<blank>" = "No",
"In this instance, the European Commission asked EU citizens and interest groups to submit their views on the topic." = "Yes",
"All national governments voted in favor." = "Unanimity",
"Most national governments voted in favor including the [COUNTRY] government, some voted against the decision." = "Majority incl. government",
"Most national governments voted in favor, some voted against the decision including the [COUNTRY] government." = "Majority not incl. government",
"Most" = "Large majority",
"Slightly more than half" = "Slight majority",
"Most EU citizens oppose this decision" = "No",
"Most EU citizens support this decision" = "Yes",
" most [NATIONALITY] support it" = "Yes",
" most [NATIONALITY] oppose it" = "No")
label_changes_topics=c("<blank>" = "No",
"Most EU citizens support this decision, most [NATIONALITY] support it" = "EU support, national support",
"Most EU citizens oppose this decision, most [NATIONALITY] support it" = "EU oppose, national support",
"Most EU citizens support this decision, most [NATIONALITY] oppose it" = "EU support, national oppose",
"Most EU citizens oppose this decision, most [NATIONALITY] oppose it" = "EU oppose, national oppose")
theme_demos <- theme(plot.title = element_text(face="bold"),
axis.text=element_text(colour="black"),
axis.title=element_text(size=8),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.title = element_blank())
theme_voting <-   theme(plot.title = element_text(face="bold"),
axis.title=element_text(size=8),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.position = "bottom",
legend.title = element_blank(),
axis.text.x = element_text(angle = 45, hjust = 1))
theme_results <-  theme(plot.title = element_text(face="bold"),
axis.text=element_text(colour="black"),
axis.title=element_text(size=8,colour="black"),
strip.text.y = element_text(angle = 0, face="bold"),
strip.background = element_blank(),
panel.border = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank(),
panel.spacing.x = unit(0,"line"),
legend.position = "bottom",
legend.title = element_blank())
#### Figure I12 ####
mm_by_topicimpression_vignette1=cj(eudata_long %>% filter(vignette=="Vignette 1"), legitimate ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, id = ~UUID, by = ~topic_impression_rec_median, estimate = "mm")
names(mm_by_topicimpression_vignette1)[names(mm_by_topicimpression_vignette1)=="level"]="term"
names(mm_by_topicimpression_vignette1)[names(mm_by_topicimpression_vignette1)=="topic_impression_rec_median"]="model"
mm_by_topicimpression_vignette1$feature <- mm_by_topicimpression_vignette1$feature %>%
recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
mm_by_topicimpression_vignette1$feature <- factor(mm_by_topicimpression_vignette1$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
mm_by_topicimpression_vignette1 = mm_by_topicimpression_vignette1 %>% filter(grepl("Sociotropic",feature))
mech_2_vignette1 <- dwplot(mm_by_topicimpression_vignette1,dot_args = list(size = 2,aes(shape = model)),whisker_args = list(aes(linetype = model))) %>%
relabel_predictors(label_changes) +
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
expand_limits(x=c(4,4.6))+
ggtitle("Vignette 1") +
scale_colour_grey(start = 0.25, end = .6) +
theme_results
mm_by_topicimpression_vignette2_5=cj(eudata_long %>% filter(vignette%in%c("Vignette 2","Vignette 3",
"Vignette 4","Vignette 5")),
legitimate ~
consult +
council+
ep +
eu_opinion +
national_opinion +
congruence, id = ~UUID, by = ~topic_impression_rec_median, estimate = "mm")
names(mm_by_topicimpression_vignette2_5)[names(mm_by_topicimpression_vignette2_5)=="level"]="term"
names(mm_by_topicimpression_vignette2_5)[names(mm_by_topicimpression_vignette2_5)=="topic_impression_rec_median"]="model"
mm_by_topicimpression_vignette2_5$feature <- mm_by_topicimpression_vignette2_5$feature %>%
recode("congruence" = "Egotropic representation",
"consult" = "Consultation",
"council" = "Voting in Council",
"ep" = "Voting in EP",
"eu_opinion" = "Sociotropic representation (EU-wide)",
"national_opinion" = "Sociotropic representation (national)")
mm_by_topicimpression_vignette2_5$feature <- factor(mm_by_topicimpression_vignette2_5$feature, levels = c("Egotropic representation",
"Sociotropic representation (EU-wide)",
"Sociotropic representation (national)",
"Consultation",
"Voting in Council",
"Voting in EP"))
mm_by_topicimpression_vignette2_5 = mm_by_topicimpression_vignette2_5 %>% filter(grepl("Sociotropic",feature))
mech_2_vignette2_5 <- dwplot(mm_by_topicimpression_vignette2_5,dot_args = list(size = 2,aes(shape = model)),whisker_args = list(aes(linetype = model))) %>%
relabel_predictors(label_changes) +
facet_grid(feature~.,scales = "free",space = "free",labeller = label_wrap_gen(width=20))+
theme_bw() +
xlab("Marginal Mean of Thinking Decision Is Legitimate") +
ylab("") +
expand_limits(x=c(4,4.6))+
ggtitle("Vignette 2,3,4 and 5") +
scale_colour_grey(start = 0.25, end = .6) +
theme_results
# This is Figure I12
gridExtra::grid.arrange(mech_2_vignette1,mech_2_vignette2_5,ncol=2)
