library(foreign)
library(arm)

nes <- read.dta("nes5200_processed_voters_realideo.dta")

nes.1976c <- na.omit(nes[which(nes$year == 1976), c("ideo7", "black", "female", "rep_pres_intent", "presapprov", "age", "educ1", "urban", "perfin1")])

glm.1976c <- glm(rep_pres_intent ~ ideo7+black+female+presapprov+age+educ1+urban+perfin1, data = nes.1976c, family = binomial)

nes.1976n <- as.data.frame(sapply(nes.1976c, as.numeric))

glm.1976n <- glm(rep_pres_intent ~ ideo7+black+female+presapprov+age+educ1+urban+perfin1, data = nes.1976n, family = binomial)

nes.2000c <- na.omit(nes[which(nes$year == 2000), c("ideo7", "black", "female", "rep_pres_intent", "presapprov", "age", "educ1", "urban", "perfin1")])

glm.2000c <- glm(rep_pres_intent ~ ideo7+black+female+presapprov+age+educ1+urban+perfin1, data = nes.2000c, family = binomial)

nes.2000n <- as.data.frame(sapply(nes.2000c, as.numeric))
glm.2000n <- glm(rep_pres_intent ~ ideo7+black+female+presapprov+age+educ1+urban+perfin1, data = nes.2000n, family = binomial)

par(mfrow = c(2,2))
binnedplot(fitted(glm.1976c), resid(glm.1976c, type = "pearson"), main = "Binned residual plot for 1976c")
binnedplot(fitted(glm.1976n), resid(glm.1976n, type = "pearson"), main = "Binned residual plot for 1976n")
binnedplot(fitted(glm.2000c), resid(glm.2000c, type = "pearson"), main = "Binned residual plot for 2000c")
binnedplot(fitted(glm.2000n), resid(glm.2000n, type = "pearson"), main
= "Binned residual plot for 2000n")

#####


vars <-  c("ideo7", "black", "female", "rep_pres_intent", "presapprov", "age",
"educ1", "urban", "income", "union", "perfin1")

tmp.1976c <- na.omit(nes[which(nes$year == 1976), vars])
tmp.1976n <- as.data.frame(sapply(tmp.1976c, as.numeric))
tmp.2000c <- na.omit(nes[which(nes$year == 2000), vars])
tmp.2000n <- as.data.frame(sapply(tmp.2000c, as.numeric))

tmp.glm.1976c <- glm(rep_pres_intent ~ ., data=tmp.1976c, family=binomial)
tmp.glm.1976n <- glm(rep_pres_intent ~ ., data=tmp.1976n, family=binomial)
tmp.glm.2000c <- glm(rep_pres_intent ~ ., data=tmp.2000c, family=binomial)
tmp.glm.2000n <- glm(rep_pres_intent ~ ., data=tmp.2000n, family=binomial)