RStudio_ct_untitled_7CD72DFF

gg <- gss %>% 
  filter(race == 1) %>% 
  mutate(years = frcode(year >= 1985 & year <= 1990 ~ "1985-1990",
                        year >= 1991 & year <= 1995 ~ "1991-1995",
                        year >= 1996 & year <= 2000 ~ "1996-2000",
                        year >= 2001 & year <= 2005 ~ "2001-2005", 
                        year >= 2006 & year <= 2010 ~ "2006-2010", 
                        year >= 2011 & year <= 2015 ~ "2011-2015", 
                        year >= 2016 & year <= 2020 ~ "2016-2018")) %>%  
  mutate(gender = frcode(sex == 1 ~ "Men", 
                         sex == 2 ~ "Women")) %>% 
  mutate(rel = frcode(reltrad == 1 ~ "Evangelical", 
                      reltrad == 2 | reltrad == 3 | reltrad == 4 ~ "Other Christian", 
                      reltrad == 5 | reltrad == 6 ~ "Other Faith", 
                      reltrad == 7 ~ "No Religion")) %>% 
  filter(denom16 == 14) %>% 
  group_by(gender, years) %>% 
  ct(rel, wt = wtssall, show_na = FALSE)


gg %>% 
  filter(years != "NA") %>% 
  ggplot(., aes(x = 1, y = pct, fill = fct_rev(rel))) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_grid(years ~ gender, switch = "y") +
  scale_fill_d3() + 
  theme_rb() +
  theme(legend.position = "bottom") +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle = 0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.08, paste0(pct*100, '%'), '')), position = position_stack(vjust = 0.5), size = 4, family = "font", color = "black") +
  labs(x = "", y = "", title = "Where Do People Raised Southern Baptist End Up?", subtitle = "", caption = "@ryanburge\nData: GSS 1985-2018") +
  ggsave("E://genders_sbc_reltrad.png", width = 9, height = 4)


gg <- gss %>% 
  filter(denom16 == 14) %>% 
  mutate(years = frcode(year >= 1985 & year <= 1990 ~ "'85-\n'90",
                        year >= 1991 & year <= 1995 ~ "'91-\n'95",
                        year >= 1996 & year <= 2000 ~ "'96-\n'00",
                        year >= 2001 & year <= 2005 ~ "'01-\n'05", 
                        year >= 2006 & year <= 2010 ~ "'06-\n'10", 
                        year >= 2011 & year <= 2015 ~ "'11-\n'15", 
                        year >= 2016 & year <= 2020 ~ "'16-\n'18")) %>% 
  mutate(gender = frcode(sex == 1 ~ "Men", 
                         sex == 2 ~ "Women")) %>% 
  mutate(sbc = case_when(denom == 14 ~ 1, 
                         TRUE ~ 0)) %>% 
  group_by(gender, years) %>% 
  mean_ci(sbc, wt = wtssall, ci = .84) %>% 
  mutate(type = "Born SBC - Stayed SBC") %>% 
  na.omit()



gg1 <- gss %>% 
  filter(denom16 == 22) %>% 
  mutate(years = frcode(year >= 1985 & year <= 1990 ~ "'85-\n'90",
                        year >= 1991 & year <= 1995 ~ "'91-\n'95",
                        year >= 1996 & year <= 2000 ~ "'96-\n'00",
                        year >= 2001 & year <= 2005 ~ "'01-\n'05", 
                        year >= 2006 & year <= 2010 ~ "'06-\n'10", 
                        year >= 2011 & year <= 2015 ~ "'11-\n'15", 
                        year >= 2016 & year <= 2020 ~ "'16-\n'18")) %>% 
  mutate(gender = frcode(sex == 1 ~ "Men", 
                         sex == 2 ~ "Women")) %>% 
  mutate(sbc = case_when(denom == 22 ~ 1, 
                         TRUE ~ 0)) %>% 
  group_by(gender, years) %>% 
  mean_ci(sbc, wt = wtssall, ci = .84) %>% 
  mutate(type = "Born UMC - Stayed UMC") %>% 
  na.omit()



gg2 <- gss %>% 
  filter(relig16 == 2) %>% 
  mutate(years = frcode(year >= 1985 & year <= 1990 ~ "'85-\n'90",
                        year >= 1991 & year <= 1995 ~ "'91-\n'95",
                        year >= 1996 & year <= 2000 ~ "'96-\n'00",
                        year >= 2001 & year <= 2005 ~ "'01-\n'05", 
                        year >= 2006 & year <= 2010 ~ "'06-\n'10", 
                        year >= 2011 & year <= 2015 ~ "'11-\n'15", 
                        year >= 2016 & year <= 2020 ~ "'16-\n'18")) %>% 
  mutate(gender = frcode(sex == 1 ~ "Men", 
                         sex == 2 ~ "Women")) %>% 
  mutate(sbc = case_when(relig == 2 ~ 1, 
                         TRUE ~ 0)) %>% 
  group_by(gender, years) %>% 
  mean_ci(sbc, wt = wtssall, ci = .84) %>% 
  mutate(type = "Born Catholic - Stayed Catholic") %>% 
  na.omit()

graph <- bind_rows(gg, gg1, gg2)

graph %>% 
  ggplot(., aes(x = years, y = mean, fill = gender)) +
  geom_col(color = "black", position = "dodge") +
  facet_wrap(~ type) +
  error_bar() +
  y_pct() + 
  theme_rb(legend = TRUE) +
  scale_fill_npg() + 
  labs(x = "", y= "", title = "Denominational Retention Rates by Gender", caption = "@ryanburge\nData: CCES 1985-2018") +
  ggsave("E://retention_by_gender.png", type = "cairo-png")