ethnocentric_dating.R

### REPLICATION OF DUNKEL AND DUTTON 2016
# Religiosity as a predictor of in-group favoritism within and between religious groups
# This assumes you have the OKCupid data loaded as d_main with various variables already created.

# recode ------------------------------------------------------------------
#own race preference
d_main$prefer_own_race = (d_main$q123 == "Yes") %>% as.factor()
table(d_main$prefer_own_race)

#religious
table(d_main$q41)
d_main$religion_seriousness = factor(d_main$q41, levels = rev(levels(d_main$q41)))

#politics
d_main$ideology = d_main$q212813

#age
d_main$age = d_main$d_age

#ideology x race
d_main$ideology_race = (d_main$race + " + " + d_main$ideology) %>% as.factor()
d_main$ideology_race = relevel(d_main$ideology_race, ref = "White + Liberal / Left-wing")
table(d_main$ideology_race)

#gender x race
d_main$race_gender = (d_main$race + " + " + d_main$gender) %>% as.factor()
d_main$race_gender = relevel(d_main$race_gender, ref = "White + Man")
table(d_main$race_gender)

# fit ---------------------------------------------------------------------
v_vars = c("prefer_own_race", "age", "gender", "race", "CA", "ideology", "religion_seriousness")

#main fit
glm("prefer_own_race ~ age + gender + race + CA + ideology + religion_seriousness", data = d_main, family = binomial()) %>% 
  MOD_summary(kfold = F) #does not work yet

#Jayman request
glm("prefer_own_race ~ age + gender + CA + religion_seriousness + ideology_race", data = d_main, family = binomial()) %>% 
  MOD_summary(kfold = F) #does not work yet

glm("prefer_own_race ~ age + CA + religion_seriousness + ideology + race_gender", data = d_main, family = binomial()) %>% 
  MOD_summary(kfold = F) #does not work yet