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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)
## load data from psre package
data(wvs)
## keep only the variables of interest in the investigation.
tmp <- wvs %>%
select(resemaval, moral, pct_univ_degree, pct_female, pct_low_income, sacsecval) %>%
dplyr::filter(resemaval > 0 & moral > 0 & sacsecval > 0 ) %>%
mutate(across(contains("pct"), ~.x*100))
## make the plot with the lsa() function from the psre package.
lsa(
formula = as.formula(sacsecval ~ resemaval + moral + pct_univ_degree +
pct_female + pct_low_income),
xlabels = c("Emancipative Vals", "Moral Perm",
"% Univ Degree", "% Female", "% Low Income"),
ylab = "Secular Values",
data=tmp)
# ggssave("output/f4_15.png", height=3.5, width=12, dpi=300)
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