
# Save initial objects
initial_objects <- ls()

# Subset to men who got brainteaser wrong
subdata <- data %>% filter(woman == 0 & brainteaser_correct == 0)

sd1 <- lm_lin(gender_identity ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)


sd2 <- lm_lin(warmth_transgender ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)


sd3 <- lm_lin(warmth_ethnic_outgroup ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)

sd4 <- lm_lin(warmth_ethnic_ingroup ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)


sd5 <- lm_lin(warmth_partisan_outgroup ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)

sd6 <- lm_lin(warmth_partisan_ingroup ~ treatment,
              covariates = reformulate(covariates_with), data = subdata) %>% 
  tidy() %>%
  filter(term == "treatment") %>%
  pull(std.error)

outcomes <- c("gender_identity",
              "warmth_transgender",
              "warmth_ethnic_outgroup",
              "warmth_ethnic_ingroup",
              "warmth_partisan_outgroup",
              "warmth_partisan_ingroup")

sds <- c(sd1, sd2, sd3, sd4, sd5, sd6)


control_sd <- sapply(outcomes, function(x) sd(subdata[subdata$treatment==0,x] %>% unlist(), na.rm = T))

table_data <- data.frame(outcomes = outcomes,
                         sds = sds,
                         test = c("two-tailed",
                                  "two-tailed",
                                  "one-tailed",
                                  "one-tailed",
                                  "one-tailed",
                                  "one-tailed"),
                         control_sd = control_sd)

table_data <- table_data %>% 
  mutate(mde = case_when(test == "two-tailed" ~ sds*2.8/control_sd,
                         test == "one-tailed" ~ sds*2.486/control_sd)) %>%
  select(test, mde) 


rownames(table_data) <- c("Gender Identity",
                          "Warmth Transgender",
                          "Warmth Ethnic Outgroup",
                          "Warmth Ethnic Ingroup",
                          "Warmth Partisan Outgroup",
                          "Warmth Partisan Ingroup")

table_data <- data.frame(
  `Hypothesis Test` = table_data$test,
  `MDE (in control SD)` = table_data$mde,
  check.names = FALSE
)

rownames(table_data) <- c("Gender Identity",
                          "Warmth Transgender",
                          "Warmth Ethnic Outgroup",
                          "Warmth Ethnic Ingroup",
                          "Warmth Partisan Outgroup",
                          "Warmth Partisan Ingroup")

export_table <- xtable(table_data, digits = c(0, 0, 3))
align(export_table) <- c("l", "c", "c")

print.xtable(
  export_table,
  file = "03_output/Table_A7.tex",
  include.rownames = TRUE,
  sanitize.colnames.function = identity
)
resizetable_cov("03_output/Table_A7.tex")

break

# Remove objects created in this file
rm(list = setdiff(ls(), initial_objects))
