Seeing Shifts in Party ID among BA Prots

ba_pid_long.R

c06 <- cces06 %>% 
  select(baprot, v2005, v4034) %>% 
  rename(race = v2005) %>% 
  rename(pid3 = v4034) %>% 
  mutate(year = "2006")

c08 <- cces08 %>% 
  select(baprot, V211, CC307) %>% 
  rename(race = V211) %>%
  rename(pid3 = CC307) %>% 
  mutate(year = "2008")

c10 <- cces10 %>% 
  select(baprot, V211, V212a) %>% 
  rename(race = V211) %>%
  rename(pid3 = V212a) %>% 
  mutate(year = "2010")

c12 <- cces12 %>% 
  select(baprot, race, pid3) %>% 
  mutate(year = "2012")

c14 <- cces14 %>% 
  select(baprot, race, pid3) %>% 
  mutate(year = "2014") 
  

c16 <- cces16 %>% 
  select(baprot, race, pid3) %>% 
  mutate(year = "2016")  
  

all <- bind_rows(c06, c08, c10, c12, c14, c16) 

## White Graph ####

rep <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==1 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "2=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Republican")

dem <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==1 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "1=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Democrat")

ind <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==1 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "3=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Independent")
  
wht_ba <- bind_rows(rep, dem, ind)

pd <- position_dodge(0.2)


wht_ba %>% 
  ggplot(., aes(x=year, y=mean, group = party, color = party)) + geom_point() + geom_line(size = 1.25) +
  geom_errorbar(aes(ymin=lower, ymax = upper), width = 0,  size = 1.25) +
  long_rb() +
  scale_y_continuous(labels = scales::percent) +
  scale_color_manual(values=c("dodgerblue3", "gray", "firebrick3")) +
  theme(plot.title = element_text(size =24)) +
  labs(x = "Year", y = "Percent of Population", title = "The Change in Partisanship Among White Born-Again Protestants", caption = "Data: CCES 2006-2016")

ggsave(file="D://cces/comparing_pid3_white1.png", type = "cairo-png", width = 12, height = 6)

## All Graph ####


rep <- all %>% 
  filter(pid3 <4) %>% 
  filter(baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "2=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Republican")

dem <- all %>% 
  filter(pid3 <4) %>% 
  filter(baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "1=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Democrat")

ind <- all %>% 
  filter(pid3 <4) %>% 
  filter(baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "3=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Independent")

ba <- bind_rows(rep, dem, ind)

pd <- position_dodge(0.2)


ba %>% 
  ggplot(., aes(x=year, y=mean, group = party, color = party)) + geom_point() + geom_line(size = 1.25) +
  geom_errorbar(aes(ymin=lower, ymax = upper), width = 0,  size = 1.25) +
  long_rb() +
  scale_y_continuous(labels = scales::percent) +
  scale_color_manual(values=c("dodgerblue3", "gray", "firebrick3")) +
  theme(plot.title = element_text(size =24)) +
  labs(x = "Year", y = "Percent of Population", title = "The Change in Partisanship Among Born-Again Protestants", caption = "Data: CCES 2006-2016")

ggsave(file="D://cces/comparing_pid3_all.png", type = "cairo-png", width = 12, height = 6)

## Black Graph ####

rep <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==2 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "2=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Republican")

dem <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==2 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "1=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Democrat")

ind <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==2 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "3=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Independent")

blk_ba <- bind_rows(rep, dem, ind)


blk_ba %>% 
  ggplot(., aes(x=year, y=mean, group = party, color = party)) + geom_point() + geom_line(size = 1.25) +
  geom_errorbar(aes(ymin=lower, ymax = upper), width = 0,  size = 1.25) +
  long_rb() +
  scale_y_continuous(labels = scales::percent) +
  scale_color_manual(values=c("dodgerblue3", "gray", "firebrick3")) +
  theme(plot.title = element_text(size =24)) +
  labs(x = "Year", y = "Percent of Population", title = "The Change in Partisanship Among Black Born-Again Protestants", caption = "Data: CCES 2006-2016")

ggsave(file="D://cces/comparing_pid3_black1.png", type = "cairo-png", width = 12, height = 6)

## Hispanic Graph ####

rep <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==3 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "2=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Republican")

dem <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==3 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "1=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Democrat")

ind <- all %>% 
  filter(pid3 <4) %>% 
  filter(race ==3 & baprot ==1) %>% 
  mutate(pid1 = recode(pid3, "3=1; else=0")) %>%  
  group_by(year) %>% 
  summarise(mean = mean(pid1),
            sd = sd(pid1), 
            n = n()) %>% 
  mutate(se = sd/sqrt(n),
         lower = mean - qt(1 - (0.05 /2),  n -1) * se,
         upper = mean + qt(1 - (0.05 /2),  n -1) * se) %>% 
  mutate(party = "Independent")

hisp_ba <- bind_rows(rep, dem, ind)


hisp_ba %>% 
  ggplot(., aes(x=year, y=mean, group = party, color = party)) + geom_point() + geom_line(size = 1.25) +
  geom_errorbar(aes(ymin=lower, ymax = upper), width = 0,  size = 1.25) +
  long_rb() +
  scale_y_continuous(labels = scales::percent) +
  scale_color_manual(values=c("dodgerblue3", "gray", "firebrick3")) +
  theme(plot.title = element_text(size =24)) +
  labs(x = "Year", y = "Percent of Population", title = "The Change in Partisanship Among Hispanic Born-Again Protestants", caption = "Data: CCES 2006-2016")

ggsave(file="D://cces/comparing_pid3_hisp1.png", type = "cairo-png", width = 12, height = 6)