RStudio_ct_selection_untitled_202BAADE

### Figure 1 ####


gg <- gss %>% 
  filter(year <= 2018) %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, reltrad) %>% 
  mean_ci(abany, wt = wtssall, ci = .84) %>% 
  na.omit() 


gg1 <- gss %>% 
  filter(year == 2021) %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, reltrad) %>% 
  mean_ci(abany, wt =wtssnrps, ci = .84) %>% 
  na.omit() 


gg2 <- gss %>% 
  filter(year <= 2018) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(abany, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(reltrad = "Entire Sample")


gg3 <- gss %>% 
  filter(year == 2021) %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year) %>% 
  mean_ci(abany, wt =wtssnrps, ci = .84) %>% 
  na.omit() %>% 
  mutate(reltrad =  "Entire Sample")

graph <- bind_rows(gg, gg1, gg2, gg3)

graph %>% 
  filter(reltrad == "Catholic" | reltrad == "Entire Sample") %>% 
  ggplot(., aes(x = year, y = mean, color = reltrad, group = reltrad)) +
  geom_point(stroke = 1, shape = 21, alpha = .25) +
  theme_rb() +
  scale_y_continuous(labels = percent, limits = c(0, .60)) +
  scale_color_manual(values = c("#412f88", "#fe5308")) +
  geom_labelsmooth(aes(label = reltrad, linetype = reltrad),  method = "loess", formula = y ~ x, family = "font", linewidth = 1, text_smoothing = 30, size = 4, linewidth = 1, boxlinewidth = 0.3) + 
  labs(x = "Year", y = "Share in Favor", title = "In Favor of A Legal Abortion if a Woman Wants One for Any Reason", caption = "@ryanburge\nData: GSS 1972-2021") +
  save("reltrad_ab_gss.png")
  
### Figure 2 ####

gg <- gss %>% 
  filter(reltrad == 4) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(year <= 2018) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, pid3) %>% 
  mean_ci(abany, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(type = "Catholics")


gg1 <- gss %>%
  filter(reltrad == 4) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  filter(year == 2021) %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, pid3) %>% 
  mean_ci(abany, wt =wtssnrps, ci = .84) %>% 
  na.omit() %>% 
  mutate(type = "Catholics")


gg2 <- gss %>% 
  filter(year <= 2018) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, pid3) %>% 
  mean_ci(abany, wt = wtssall, ci = .84) %>% 
  na.omit() %>% 
  mutate(type = "Entire Sample")


gg3 <- gss %>% 
  filter(year == 2021) %>% 
  mutate(pid7 = partyid + 1) %>% 
  cces_pid3(pid7) %>% 
  mutate(abany = case_when(abany == 1 ~ 1, abany == 2 ~ 0)) %>% 
  group_by(year, pid3) %>% 
  mean_ci(abany, wt =wtssnrps, ci = .84) %>% 
  na.omit() %>% 
  mutate(type =  "Entire Sample")

graph <- bind_rows(gg, gg1, gg2, gg3)

graph %>% 
  ggplot(., aes(x = year, y = mean, color = type, group = type, linetype = type)) +
  geom_point(stroke = 1, shape = 21, alpha = .25) +
  theme_rb(legend = TRUE) +
  facet_wrap(~ pid3) +
  scale_y_continuous(labels = percent) +
  scale_color_manual(values = c("#412f88", "#fe5308")) +
  geom_smooth(se = FALSE) +
  labs(x = "Year", y = "Share in Favor", title = "In Favor of A Legal Abortion if a Woman Wants One for Any Reason", caption = "@ryanburge\nData: GSS 1972-2021") +
  save("pid3_ab_gss.png")

## Figure 3 ####

gg <- cces %>% 
  filter(trad2 == "White Catholic" | trad2 == "Non-White Catholic") %>% 
  cces_attend(pew_churatd) %>% 
  cces_pid3(pid7) %>% 
  mutate(ab = case_when(ab_choice == 1 ~ 1, ab_choice == 2 ~ 0)) %>% 
  group_by(att, year, pid3) %>% 
  mean_ci(ab, wt = weight, ci = .84)

gg1 <- cces21 %>% 
  filter(religpew == 2) %>% 
  cces_pid3(pid7) %>% 
  cces_attend(pew_churatd) %>% 
  mutate(ab = case_when(CC21_323a == 1 ~ 1, CC21_323a == 2 ~ 0)) %>% 
  group_by(att, pid3) %>% 
  mean_ci(ab, wt = commonweight, ci = .84) %>% 
  mutate(year = 2021) 

graph <- bind_rows(gg, gg1) %>% filter(pid3 != "NA")

graph %>% 
  filter(att != "NA") %>% 
  ggplot(., aes(x = year, y = mean, color = pid3, group = pid3)) +
  # error_bar() +
  geom_point(stroke = 1, shape = 21, fill = "white", alpha = .5) + 
  geom_smooth(se = FALSE, method = lm) +
  facet_wrap(~ att) +
  scale_y_continuous(labels = percent, limits = c(0, .85)) +
  theme_rb(legend = TRUE) +
  pid3_color()+
  labs(x = "Year", y = "Share in Favor", title = "In Favor of A Legal Abortion if a Woman Wants One for Any Reason", subtitle = "Among Catholics - By Mass Attendance", caption = "@ryanburge\nData: CES 2014-2021") +
  save("cath_att_abort.png")