Nothing
options(width=72)
options(digits=3)
nes1948.por <- UnZip("anes/NES1948.ZIP","NES1948.POR",package="codebooks")
nes1948 <- spss.portable.file(nes1948.por)
print(nes1948)
names(nes1948)
codebook(nes1948)
vote.48 <- subset(nes1948,
select=c(
v480018,
v480029,
v480030,
v480045,
v480046,
v480047,
v480048,
v480049,
v480050
))
str(vote.48)
vote.48 <- rename(vote.48,
v480018 = "vote",
v480029 = "occupation.hh",
v480030 = "unionized.hh",
v480045 = "gender",
v480046 = "race",
v480047 = "age",
v480048 = "education",
v480049 = "total.income",
v480050 = "religious.pref"
)
codebook(vote.48)
vote.48 <- within(vote.48,{
vote3 <- recode(vote,
1 -> "Truman",
2 -> "Dewey",
3:4 -> "Other"
)
occup4 <- recode(occupation.hh,
10:20 -> "Upper white collar",
30 -> "Other white collar",
40:70 -> "Blue collar",
80 -> "Farmer"
)
relig3 <- recode(religious.pref,
1 -> "Protestant",
2 -> "Catholic",
3:5 -> "Other,none"
)
race2 <- recode(race,
1 -> "White",
2 -> "Black"
)
})
xtabs(~vote3+occup4,data=vote.48)
t(genTable(percent(vote3)~occup4,data=vote.48))
t(genTable(percent(vote3)~relig3,data=vote.48))
t(genTable(percent(vote3)~race2,data=vote.48))
t(genTable(percent(vote3)~total.income,data=vote.48))
print(agg.inc <- aggregate(percent(vote3,ci=TRUE)~total.income,data=vote.48))
if(interactive())
old.prompt <- devAskNewPage(TRUE)
xyplot(cbind(Percentage,upper,lower)~total.income,
data=subset(agg.inc,vote3=="Truman"),
panel=panel.errbars,
xlab="Household income",
ylab="Percentage voting for Truman",
pch=19,ewidth=0.025,
scales=list(x=list(
rot=90
)),
)
agg.occup <- aggregate(percent(vote3,ci=TRUE)~occup4,data=vote.48)
xyplot(cbind(Percentage,upper,lower)~occup4,
data=subset(agg.occup,vote3=="Truman"),
panel=panel.errbars,
xlab="Occupation head of household",
ylab="Percentage voting for Truman",
pch=19,ewidth=0.025,
scales=list(x=list(
rot=90
)),
)
if(interactive())
devAskNewPage(old.prompt)
vote.48 <- within(vote.48,{
numeric.t.income <- as.numeric(total.income)
contrasts(occup4) <- contr("treatment",base = 3)
contrasts(total.income) <- contr("treatment",base = 4)
})
model1 <- glm((vote3=="Truman")~occup4,data=vote.48,
family="binomial")
model2 <- glm((vote3=="Truman")~numeric.t.income,data=vote.48,
family="binomial")
model3 <- glm((vote3=="Truman")~occup4+numeric.t.income,data=vote.48,
family="binomial")
model4 <- glm((vote3=="Truman")~total.income,data=vote.48,
family="binomial")
model5 <- glm((vote3=="Truman")~occup4+total.income,data=vote.48,
family="binomial")
model6 <- glm((vote3=="Truman")~relig3,data=vote.48,
family="binomial")
model7 <- glm((vote3=="Truman")~occup4+relig3,data=vote.48,
family="binomial")
mtable(model1,model2,model3,summary.stats=c("Deviance","AIC","N"))
mtable(model1,model4,model5,summary.stats=c("Deviance","AIC","N"))
mtable(model1,model6,model7,summary.stats=c("Deviance","AIC","N"))
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