ct_selection_untitled-8E0335D0.R

library(rio)
library(janitor)

ch <- import("E://data/chapman21.sav") %>% clean_names()




# List of questions and their respective labels
questions <- list(
  q20a = "Aliens",
  q20b = "9/11 Attacks",
  q20c = "South Dakota Crash",
  q20d = "Global Warming",
  q20e = "JFK Assassination",
  q20f = "Moon Landing",
  q20g = "Illuminati/New World Order",
  q20h = "Mass Shootings",
  q20i = "Q'Anon"
)

# Function to calculate mean and confidence intervals
calculate_ci <- function(data, question, label) {
  data %>%
    mutate(qq = case_when(
      !!sym(question) == 1 | !!sym(question) == 2 ~ 1,  # Agreement
      !!sym(question) == 3 | !!sym(question) == 4 ~ 0   # Disagreement
    )) %>%
    mean_ci(qq, wt = weight, ci = .84) %>%
    mutate(type = label)
}

# Apply the function to each question and combine results
results <- bind_rows(
  lapply(names(questions), function(q) {
    calculate_ci(ch, q, questions[[q]])
  })
)


results %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = reorder(type, mean), y = mean, fill = type)) +
  geom_col(color = "black") +
  coord_flip() +
  theme_rb() +
  error_bar() +
  y_pct() + 
  scale_fill_manual(values =met.brewer("Klimt", 9)) +
  lab_bar(top = FALSE, type = lab, pos = .05, sz = 10) +
  geom_text(aes(y = .05, label = ifelse(type == "Moon Landing", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 10, family = "font", color = "white") + 
  geom_text(aes(y = .05, label = ifelse(type == "Q'Anon", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 10, family = "font", color = "white") +  
  geom_text(aes(y = .05, label = ifelse(type == "South Dakota Crash", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 10, family = "font", color = "white") + 
  geom_text(aes(y = .05, label = ifelse(type == "Mass Shootings", paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 10, family = "font", color = "white") +   
  labs(x = "", y = "", title = "Share Agreeing the Government is Concealing What It Knows About...", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021") 
save("chapman_conspiracies_all.png")


# Function to calculate mean and confidence intervals
calculate_ci <- function(data, question, label) {
  data %>%
    mutate(qq = case_when(
      !!sym(question) == 1 | !!sym(question) == 2 ~ 1,  # Agreement
      !!sym(question) == 3 | !!sym(question) == 4 ~ 0   # Disagreement
    )) %>%
    mutate(rel = frcode(q1 == 1 ~ "Not\nat All", 
                        q1 == 2 ~ "Not\nToo", 
                        q1 == 3 ~ "Somewhat", 
                        q1 == 4 ~ "Very\nReligious")) %>% 
    group_by(rel) %>% 
    mean_ci(qq, wt = weight, ci = .84) %>%
    mutate(type = label)
}

# Apply the function to each question and combine results
results <- bind_rows(
  lapply(names(questions), function(q) {
    calculate_ci(ch, q, questions[[q]])
  })
)


palette <- c(
  "Not\nat All" = "#1f78b4",  # Blue
  "Not\nToo" = "#33a02c",     # Green
  "Somewhat" = "#e31a1c",     # Red
  "Very\nReligious" = "#ff7f00" # Orange
)


results %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = rel, y = mean, fill = rel)) +
  geom_col(color = 'black') +
  facet_wrap(~ type) +
  scale_fill_manual(values = palette) + 
  error_bar() +
  theme_rb() + 
  y_pct() + 
  lab_bar(top = FALSE, type = lab, pos = .045, sz = 7) +
  labs(x = "How Religious Are You?", y = "", title = "Share Agreeing the Government is Concealing What It Knows About...", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021") 
save("rel_fears_conspiracies_by_category.png", ht = 10, wd = 8.25)




ch <- ch %>%
  mutate(across(starts_with("q20"), ~ dplyr::recode(.,
                                                    `1` = 1, # Strongly agree
                                                    `2` = 1, # Agree
                                                    `3` = 0, # Disagree
                                                    `4` = 0, # Strongly disagree
                                                    .default = NA_real_))) %>%
  rowwise() %>%
  mutate(con_index = sum(c_across(starts_with("q20")), na.rm = TRUE)) %>%
  ungroup() 



graph <- ch %>% 
  mutate(rel = frcode(q1 == 1 ~ "Not\nat All", 
                      q1 == 2 ~ "Not\nToo", 
                      q1 == 3 ~ "Somewhat", 
                      q1 == 4 ~ "Very\nReligious")) %>% 
  group_by(rel) %>% 
  mean_ci(con_index, wt = weight, ci = .84)

palette <- c(
  "Not\nat All" = "#1f78b4",  # Blue
  "Not\nToo" = "#33a02c",     # Green
  "Somewhat" = "#e31a1c",     # Red
  "Very\nReligious" = "#ff7f00" # Orange
)


graph %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = rel, y = mean, fill = rel)) +
  geom_col(color = "black") +
  theme_rb() +
  error_bar() + 
  scale_fill_manual(values = palette) +  # Apply the custom color palette
  geom_text(aes(y = .5, label = lab), position = position_dodge(width = .9), size = 12, family = "font") +
  labs(x = "How Religious Are You?", y = "Number of Conspiracies Embraced", title = "Is There a Relationship Between Religiosity\nand Conspiratorial Thinking?", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021") 
save("rel_conspiracy_chapman.png", wd = 5)



graph <- ch %>% 
  mutate(att = q2) %>% 
  mutate(att = frcode(att == 1 ~ "Never", 
                      att == 2 ~ "Special\nOccasions", 
                      att == 3 | att == 4 | att == 5 ~ "Yearly", 
                      att == 6 | att == 7 ~ "Monthly", 
                      att == 8 | att == 9 ~ "Weekly")) %>% 
  group_by(att) %>% 
  mean_ci(con_index, wt = weight, ci = .84)

palette <- c(
  "Never" = "#a6cee3",                # Light Blue
  "Special\nOccasions" = "#b2df8a", # Light Green
  "Yearly" = "#fb9a99",              # Light Red
  "Monthly" = "#fdbf6f",             # Light Orange
  "Weekly" = "#cab2d6"               # Light Purple
)


graph %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = att, y = mean, fill = att)) +
  geom_col(color = "black") +
  theme_rb() +
  error_bar() + 
  scale_fill_manual(values = palette) +  # Apply the custom color palette
  geom_text(aes(y = .5, label = lab), position = position_dodge(width = .9), size = 11, family = "font") +
  labs(x = "How Often Do You Attend Religious Services?", y = "Number of Conspiracies Embraced", title = "Is There a Relationship Between Religious Attendance\nand Conspiratorial Thinking?", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021") 
save("att_conspiracy_chapman.png", wd = 5.5)





ch <- ch %>%
  mutate(across(starts_with("q20"), ~ dplyr::recode(.,
                                                    `1` = 1, # Strongly agree
                                                    `2` = 1, # Agree
                                                    `3` = 0, # Disagree
                                                    `4` = 0, # Strongly disagree
                                                    .default = NA_real_))) %>%
  rowwise() %>%
  mutate(con_index = sum(c_across(starts_with("q20")), na.rm = TRUE)) %>%
  ungroup() 

reg <- ch %>% 
  mutate(married = case_when(i_marital == 3 ~ 1, 
                             TRUE ~ 0)) %>% 
  mutate(white = case_when(i_race == 1 ~ 1, 
                           TRUE ~ 0)) %>% 
  mutate(male = case_when(i_sex == 1 ~ 1, 
                          i_sex == 2 ~ 0)) %>% 
  mutate(cons = case_when(q4 == 1 | q4 == 2 | q4 == 3 ~ 1, 
                          q4 <= 7 ~ 0)) %>% 
  mutate(literal = case_when(q3 == 1 ~ 1, 
                             q3 == 2 | q3 == 3 | q3 == 4 | q3 == 5 ~ 0)) %>% 
  select(con_index, attend = q2, literal, cons, married, white, male, age = i_age, educ)

out <- glm(con_index ~ ., data = reg)



coef_names <- c("White" = "white", 
                "Education" = "educ", 
                "Age" = "age", 
                "Male" = "male", 
                "Married" = "married", 
                "Church Attendance" = "attend", 
                "Biblical Literalism" = "literal",
                "Politically Conservative" = "cons")

out <- plot_summs(out, scale = TRUE, robust = "HC3", colors = "firebrick3", coefs = coef_names)



out + 
  theme_rb() +
  labs(x = "", y = "", title = "What Factors Predict Stronger Conspiratorial Thinking?", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021") 
# add_text(x = -9, y = 3.5, word = "Lower Fear Index", sz = 6) 
save("conspiracy_plot_summs_chapman.png", ht = 4, wd = 9.5)



reg <- ch %>% 
  mutate(married = case_when(i_marital == 3 ~ 1, 
                             TRUE ~ 0)) %>% 
  mutate(white = case_when(i_race == 1 ~ 1, 
                           TRUE ~ 0)) %>% 
  mutate(male = case_when(i_sex == 1 ~ 1, 
                          i_sex == 2 ~ 0)) %>% 
  mutate(id7 = 8-q4) %>% 
  mutate(bible = frcode(q3 == 1 ~ "Literal", 
                        q3 == 2 ~ "Inspired, Not Literal", 
                        q3 == 3 ~ "Some Errors", 
                        q3 == 4 ~ "History and Legends")) %>% 
  mutate(literal = case_when(q3 == 1 ~ 1, 
                             q3 == 2 | q3 == 3 | q3 == 4 | q3 == 5 ~ 0)) %>% 
  select(con_index, attend = q2,  bible, id7, married, white, male, age = i_age, educ)

out <- glm(con_index ~ bible*id7 + ., data = reg)

library(interactions)

pp <- interact_plot(out, pred= id7, modx = bible, int.width = .76, interval = TRUE) 

pp +
  theme_rb(legend = TRUE) +
  scale_x_continuous(breaks = c(1,2,3,4,5,6,7), labels = c("Extremely\nLiberal", "Liberal", "Leaning\nLiberal", 
                                                           "Moderate", 
                                                           "Leaning\nConservative", "Conservative", "Extremely\nConservative")) +
  labs(x = "Political Ideology", y = "Average Number of Conspiracies Embraced", title = "Interaction of Political Ideology and Views of the Bible on Conspiratorial Thinking", 
       caption = "@ryanburge + @religiondata\nData: Chapman Survey of American Fears, 2021")
save("con_thinking_inteaction_bible_id7.png", ht = 8)