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## The psre package must be installed first.
## You can do this with the following code
# install.packages("remotes")
# remotes::install_github('davidaarmstrong/psre')
## load packages
library(tidyverse)
library(psre)
library(DAMisc)
## load data from psre package
data(wvs)
## keep only those countries where there are some
## people with a university degree
wvs2 <- wvs %>% filter(pct_univ_degree > 0)
## estimate model
intmod4 <- lm(resemaval ~ gini_disp*pct_high_rel_imp, data=wvs)
## generate data giving the conditional effects
## of each continuous variable given the values
## of the other.
plot.dat <- DAintfun2(intmod4, c("gini_disp", "pct_high_rel_imp"), plot.type = "none")
## A. Gini coefficient given religious importance
## main panel
e1a <- ggplot(data=plot.dat,
aes(x=vals_pct_high_rel_imp, y = eff_gini_disp, ymin=low_gini_disp, ymax=up_gini_disp)) +
geom_ribbon(alpha=.25) +
geom_line() +
theme_classic() +
labs(x="Religious Importance",
y = "Conditional Effect of Gini Coefficient")
## get range of y-axis from main panel
p1 <- ggplot_build(e1a)
rgy <- p1$layout$panel_params[[1]]$y.range
maxy <- rgy[1] + .3*diff(rgy)
## histogram for panel A
e1b <- ggplot(data=wvs,
aes(x=pct_high_rel_imp)) +
geom_histogram(bins=15, col="white") +
theme_void()
e1bgrob <- ggplotGrob(e1b)
## put histogram in main panel
e1 <- e1a +
geom_hline(yintercept=0, lty=2, col="gray50") +
annotation_custom(e1bgrob, ymax=maxy)
e1
# ggssave("output/f9_5a.png", height=4.5, width=4.5, units="in", dpi=300)
## B. Religious importance given gini coefficient
## proceed as above
e2a <- ggplot(data=plot.dat,
aes(x=vals_gini_disp, y = eff_pct_high_rel_imp, ymin=low_pct_high_rel_imp, ymax=up_pct_high_rel_imp)) +
geom_ribbon(alpha=.25) +
geom_line() +
theme_classic() +
labs(x="Gini Coefficient",
y = "Conditional Effect of Religious Importance")
p2 <- ggplot_build(e2a)
rgy <- p2$layout$panel_params[[1]]$y.range
maxy <- rgy[1] + .3*diff(rgy)
e2b <- ggplot(data=wvs,
aes(x=gini_disp)) +
geom_histogram(bins=15) +
theme_void()
e2bgrob <- ggplotGrob(e2b)
e2 <- e2a +
geom_hline(yintercept=0, lty=2, col="gray50") +
annotation_custom(e2bgrob, ymax=maxy)
e2
# ggssave("output/f9_5b.png", height=4.5, width=4.5, units="in", dpi=300)
## Change in Significance
changeSig(intmod4, vars=c("gini_disp", "pct_high_rel_imp"))
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