primary: Data on the 2016 Republican Presidentical Primaries
In smtorres/GLMpack: Data and Code to Accompany Generalized Linear Models, 2nd Edition
Description
Usage
Format
Examples
Description
Data for the primary example used in chapters 4 and 5
Usage
1
Format
A data frame with 706 rows and 9 variables:
- PRIMVOTE
Vote intention
- AGE
Age
- GENDER
Gender
- EDUCATION
Education
- REGION
Region of the country in which the respondent lives
- RELIGIOSITY
Religiosity
- IDEOLOGY
Ideology
- RWA
Right Wing Authoritarianism scale
- TRUMPWIN
Perceptions of whether Trump could win
...
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data(primary)
attach(primary)
library(nnet)
library(pBrackets)
library(effects)
## Model
primary.out <- multinom(PRIMVOTE ~ AGE + GENDER + EDUCATION + REGION +
RELIGIOSITY + IDEOLOGY + RWA + TRUMPWIN, data=primary)
summ.primary.out <- glm.summary.multinom(primary.out)
## Figure 4.2
par(mfrow=c(3,3), mar=c(2.5,2,2,1))
# Plot 1: Electoral preference
countsPV0 <- barplot(table(primary$PRIMVOTE), main="Electoral Preference",
xlab="Candidates", mgp=c(1.1, 0.2, 1))
text(countsPV0[,1], rep(10,4), as.numeric(table(primary$PRIMVOTE)), cex=1.5)
# Plot 2: Age
countsAGE <- barplot(table(primary$AGE), main="Age",
xlab="Age categories", mgp=c(1.1, 0.2, 0))
text(countsAGE[,1], rep(10,4), as.numeric(table(primary$AGE)), cex=1.5)
# Plot 3: Gender
countsGENDER <- barplot(table(primary$GENDER), main="Gender",
xlab="Gender categories", mgp=c(1.1, 0.2, 0), ylim=c(0,500))
text(countsGENDER[,1], rep(25,2), as.numeric(table(primary$GENDER)), cex=1.5)
# Plot 4: Education
countsEDUC <- barplot(table(primary$EDUCATION), main="Education",
xlab="Schooling level", mgp=c(1.1, 0.2, 0))
text(countsEDUC[,1], rep(10,4), as.numeric(table(primary$EDUCATION)), cex=1.5)
# Plot 5: Region
countsREG <- barplot(table(primary$REGION), main="Region",
xlab="Region", mgp=c(1.1, 0.2, 0))
text(countsREG[,1], rep(10,4), as.numeric(table(primary$REGION)), cex=1.5)
hist(primary$RELIGIOSITY,xlab="Religiosity Score",ylab="",
xlim=c(-1.5,2), ylim=c(0, 225), main="Religiosity",
col = "gray70", mgp=c(1.1, 0.2, 0))
# Plot 7: Ideology
hist(primary$IDEOLOGY,xlab="Ideology Score",ylab="",
xlim=c(-2,1.5), ylim=c(0, 150), main="Ideology",
col = "gray70", mgp=c(1.1, 0.2, 0))
# Plot 8: Right Wing Authoritarianism
hist(primary$RWA,xlab="Right Wing Authoritarianism Score",ylab="",
xlim=c(-2.5,2), ylim=c(0, 200), main="Authoritarianism",
col = "gray70", mgp=c(1.1, 0.2, 0))
colnames(primary)
# Plot 9: Could Trump Win?
countsWIN <- barplot(table(primary$TRUMPWIN), main="Trump's winnability",
xlab="Perceptions of whether Trump could win",
mgp=c(1.1, 0.2, 0), ylim=c(0,550))
text(countsWIN[,1], rep(30,3), as.numeric(table(primary$TRUMPWIN)), cex=1.5)
dev.off()
## Figure 5.3
layout(matrix(1:2, ncol = 1), heights = c(0.9,0.1))
par(mar=c(3,4,0,1),oma=c(1,1,1,1))
plot(summ.primary.out[[1]][,1], type = "n", xaxt="n", yaxt="n",
xlim=c(-10,3), ylim=c(0,60), ylab="", xlab="")
abline(v=-5, h=c(12,16,28,40,44,48,52), lwd=2)
abline(h=c(4,8,20,24,32,36,56), lty=3, col="gray60")
text(rep(-7.5,15), seq(2,58,4),
labels = c('30-44', '45-59', '60+',
'Male',
'High School','Some College','Bachelor\'s degree or higher',
'Northeast', 'South', 'West',
'Religiosity',
'Ideology',
'Authoritarianism',
'Yes', 'Don\'t know'))
segments(summ.primary.out[[1]][-1,3], seq(1,57,4), summ.primary.out[[1]][-1,4],
seq(1,57,4), col="gray30", lwd=2)
points(summ.primary.out[[1]][-1,1], seq(1,57,4), pch=21, cex=1.4, bg="black")
text(summ.primary.out[[1]][-1,1], seq(1,57,4), labels = "C", cex = 0.7, col="white")
segments(summ.primary.out[[2]][-1,3], seq(3,59,4), summ.primary.out[[2]][-1,4],
seq(3,59,4), col="gray30", lwd=2)
points(summ.primary.out[[2]][-1,1], seq(3,59,4), pch=21, cex=1.4, bg="white")
text(summ.primary.out[[2]][-1,1], seq(3,59,4), labels = "K", cex = 0.7, col="black")
abline(v=0, lty=2)
axis(1, tck=0.01, at = seq(-5,5,0.5),cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0,
lwd.ticks = 1)
axis(2, tck=0.02, at = c(6,14,22,34,42,46,50,56), labels=c('AGE', 'GENDER',
'EDUCATION', 'REGION', 'RELIGIOSITY', 'IDEOLOGY', 'RWA', 'TRUMPWIN'),
cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 0, las=1)
title(xlab = "Coefficient",
line = 1.7, cex.lab=1.3)
par(mar=c(0,4,0,0))
plot(0,0, type="n", axes = FALSE, xaxt="n", yaxt="n", xlab="", ylab = "")
legend("center", c("Cruz", "Kasich"), ncol=2, pch=c(21,21), pt.bg=c("black", "white"),
pt.cex=rep(1.4,2), bty = "n")
dev.off()
## Figure 5.4
mygray = rgb(153, 153, 153, alpha = 200, maxColorValue = 255)
mygray2 = rgb(179, 179, 179, alpha = 150, maxColorValue = 255)
mygray3 = rgb(204, 204, 204, alpha = 150, maxColorValue = 255)
preds_win <- Effect("TRUMPWIN", primary.out)
preds_ideol <- Effect("IDEOLOGY", primary.out, xlevels=list(IDEOLOGY=100))
par(mfrow=c(1,2), mar=c(4,3,3,0),oma=c(1,1,1,1))
plot(1:3, preds_win$prob[,1], type="n",xlab="",ylab="", yaxt="n", xaxt="n",
xlim=c(0,4), ylim=c(0, 0.7))
segments(rep(1:3, 3), preds_win$lower.prob[,1:3], rep(1:3, 3), preds_win$upper.prob[,1:3],
col=rep(c('black', 'black', 'gray60'), each=3), lty = rep(c(1,2,1), each=3))
points(rep(1:3,3), preds_win$prob[,1:3], pch=21, cex = 2,
bg=rep(c("black", "white", "gray60"),each=3), col=rep(c("black", "black", "gray60"),each=3))
text(rep(1:3,3), preds_win$prob[,1:3], labels=rep(c("T", "C", "K"), each=3), cex = 0.8,
bg=rep(c("black", "white", "gray60"),each=3), col=rep(c("white", "black", "black"),each=3))
axis(1, at=1:3, labels = c("No", "Yes", "DK"), tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0),
lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'Perceptions of whether Trump could win the election',
ylab="Probability of voting",
line = 1.7, cex.lab=1)
title(line = 1, main="Winnability", font.main=3)
plot(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,1], type="n",xlab="",ylab="", yaxt="n", xaxt="n",
xlim=c(-2,1.5), ylim=c(0, 0.7))
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,2], rev(preds_ideol$upper.prob[,2])), border = NA, col=mygray2)
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,1], rev(preds_ideol$upper.prob[,1])), border = NA, col=mygray)
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,3], rev(preds_ideol$upper.prob[,3])), border = NA, col=mygray3)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,1], col="gray20", lwd=2)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,2], col="gray40", lwd=2, lty=2)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,3], col="black", lwd=2)
text(rep(1,3), c(min(preds_ideol$prob[,1]), min(preds_ideol$prob[,2]),
max(preds_ideol$prob[,3]))+.05, labels = c('Trump', 'Cruz', 'Kasich'))
axis(1, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'Ideology scores',
ylab="Probability of voting",
line = 1.7, cex.lab=1)
title(line = 1, main="Ideology", font.main=3)
dev.off()
smtorres/GLMpack documentation built on July 21, 2019, 10:59 p.m.
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Description Usage Format Examples
Description
Data for the primary example used in chapters 4 and 5
Usage
1 |
Format
A data frame with 706 rows and 9 variables:
- PRIMVOTE
Vote intention
- AGE
Age
- GENDER
Gender
- EDUCATION
Education
- REGION
Region of the country in which the respondent lives
- RELIGIOSITY
Religiosity
- IDEOLOGY
Ideology
- RWA
Right Wing Authoritarianism scale
- TRUMPWIN
Perceptions of whether Trump could win
...
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | data(primary)
attach(primary)
library(nnet)
library(pBrackets)
library(effects)
## Model
primary.out <- multinom(PRIMVOTE ~ AGE + GENDER + EDUCATION + REGION +
RELIGIOSITY + IDEOLOGY + RWA + TRUMPWIN, data=primary)
summ.primary.out <- glm.summary.multinom(primary.out)
## Figure 4.2
par(mfrow=c(3,3), mar=c(2.5,2,2,1))
# Plot 1: Electoral preference
countsPV0 <- barplot(table(primary$PRIMVOTE), main="Electoral Preference",
xlab="Candidates", mgp=c(1.1, 0.2, 1))
text(countsPV0[,1], rep(10,4), as.numeric(table(primary$PRIMVOTE)), cex=1.5)
# Plot 2: Age
countsAGE <- barplot(table(primary$AGE), main="Age",
xlab="Age categories", mgp=c(1.1, 0.2, 0))
text(countsAGE[,1], rep(10,4), as.numeric(table(primary$AGE)), cex=1.5)
# Plot 3: Gender
countsGENDER <- barplot(table(primary$GENDER), main="Gender",
xlab="Gender categories", mgp=c(1.1, 0.2, 0), ylim=c(0,500))
text(countsGENDER[,1], rep(25,2), as.numeric(table(primary$GENDER)), cex=1.5)
# Plot 4: Education
countsEDUC <- barplot(table(primary$EDUCATION), main="Education",
xlab="Schooling level", mgp=c(1.1, 0.2, 0))
text(countsEDUC[,1], rep(10,4), as.numeric(table(primary$EDUCATION)), cex=1.5)
# Plot 5: Region
countsREG <- barplot(table(primary$REGION), main="Region",
xlab="Region", mgp=c(1.1, 0.2, 0))
text(countsREG[,1], rep(10,4), as.numeric(table(primary$REGION)), cex=1.5)
hist(primary$RELIGIOSITY,xlab="Religiosity Score",ylab="",
xlim=c(-1.5,2), ylim=c(0, 225), main="Religiosity",
col = "gray70", mgp=c(1.1, 0.2, 0))
# Plot 7: Ideology
hist(primary$IDEOLOGY,xlab="Ideology Score",ylab="",
xlim=c(-2,1.5), ylim=c(0, 150), main="Ideology",
col = "gray70", mgp=c(1.1, 0.2, 0))
# Plot 8: Right Wing Authoritarianism
hist(primary$RWA,xlab="Right Wing Authoritarianism Score",ylab="",
xlim=c(-2.5,2), ylim=c(0, 200), main="Authoritarianism",
col = "gray70", mgp=c(1.1, 0.2, 0))
colnames(primary)
# Plot 9: Could Trump Win?
countsWIN <- barplot(table(primary$TRUMPWIN), main="Trump's winnability",
xlab="Perceptions of whether Trump could win",
mgp=c(1.1, 0.2, 0), ylim=c(0,550))
text(countsWIN[,1], rep(30,3), as.numeric(table(primary$TRUMPWIN)), cex=1.5)
dev.off()
## Figure 5.3
layout(matrix(1:2, ncol = 1), heights = c(0.9,0.1))
par(mar=c(3,4,0,1),oma=c(1,1,1,1))
plot(summ.primary.out[[1]][,1], type = "n", xaxt="n", yaxt="n",
xlim=c(-10,3), ylim=c(0,60), ylab="", xlab="")
abline(v=-5, h=c(12,16,28,40,44,48,52), lwd=2)
abline(h=c(4,8,20,24,32,36,56), lty=3, col="gray60")
text(rep(-7.5,15), seq(2,58,4),
labels = c('30-44', '45-59', '60+',
'Male',
'High School','Some College','Bachelor\'s degree or higher',
'Northeast', 'South', 'West',
'Religiosity',
'Ideology',
'Authoritarianism',
'Yes', 'Don\'t know'))
segments(summ.primary.out[[1]][-1,3], seq(1,57,4), summ.primary.out[[1]][-1,4],
seq(1,57,4), col="gray30", lwd=2)
points(summ.primary.out[[1]][-1,1], seq(1,57,4), pch=21, cex=1.4, bg="black")
text(summ.primary.out[[1]][-1,1], seq(1,57,4), labels = "C", cex = 0.7, col="white")
segments(summ.primary.out[[2]][-1,3], seq(3,59,4), summ.primary.out[[2]][-1,4],
seq(3,59,4), col="gray30", lwd=2)
points(summ.primary.out[[2]][-1,1], seq(3,59,4), pch=21, cex=1.4, bg="white")
text(summ.primary.out[[2]][-1,1], seq(3,59,4), labels = "K", cex = 0.7, col="black")
abline(v=0, lty=2)
axis(1, tck=0.01, at = seq(-5,5,0.5),cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0,
lwd.ticks = 1)
axis(2, tck=0.02, at = c(6,14,22,34,42,46,50,56), labels=c('AGE', 'GENDER',
'EDUCATION', 'REGION', 'RELIGIOSITY', 'IDEOLOGY', 'RWA', 'TRUMPWIN'),
cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 0, las=1)
title(xlab = "Coefficient",
line = 1.7, cex.lab=1.3)
par(mar=c(0,4,0,0))
plot(0,0, type="n", axes = FALSE, xaxt="n", yaxt="n", xlab="", ylab = "")
legend("center", c("Cruz", "Kasich"), ncol=2, pch=c(21,21), pt.bg=c("black", "white"),
pt.cex=rep(1.4,2), bty = "n")
dev.off()
## Figure 5.4
mygray = rgb(153, 153, 153, alpha = 200, maxColorValue = 255)
mygray2 = rgb(179, 179, 179, alpha = 150, maxColorValue = 255)
mygray3 = rgb(204, 204, 204, alpha = 150, maxColorValue = 255)
preds_win <- Effect("TRUMPWIN", primary.out)
preds_ideol <- Effect("IDEOLOGY", primary.out, xlevels=list(IDEOLOGY=100))
par(mfrow=c(1,2), mar=c(4,3,3,0),oma=c(1,1,1,1))
plot(1:3, preds_win$prob[,1], type="n",xlab="",ylab="", yaxt="n", xaxt="n",
xlim=c(0,4), ylim=c(0, 0.7))
segments(rep(1:3, 3), preds_win$lower.prob[,1:3], rep(1:3, 3), preds_win$upper.prob[,1:3],
col=rep(c('black', 'black', 'gray60'), each=3), lty = rep(c(1,2,1), each=3))
points(rep(1:3,3), preds_win$prob[,1:3], pch=21, cex = 2,
bg=rep(c("black", "white", "gray60"),each=3), col=rep(c("black", "black", "gray60"),each=3))
text(rep(1:3,3), preds_win$prob[,1:3], labels=rep(c("T", "C", "K"), each=3), cex = 0.8,
bg=rep(c("black", "white", "gray60"),each=3), col=rep(c("white", "black", "black"),each=3))
axis(1, at=1:3, labels = c("No", "Yes", "DK"), tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0),
lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'Perceptions of whether Trump could win the election',
ylab="Probability of voting",
line = 1.7, cex.lab=1)
title(line = 1, main="Winnability", font.main=3)
plot(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,1], type="n",xlab="",ylab="", yaxt="n", xaxt="n",
xlim=c(-2,1.5), ylim=c(0, 0.7))
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,2], rev(preds_ideol$upper.prob[,2])), border = NA, col=mygray2)
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,1], rev(preds_ideol$upper.prob[,1])), border = NA, col=mygray)
polygon(c(preds_ideol$x$IDEOLOGY, rev(preds_ideol$x$IDEOLOGY)),
c(preds_ideol$lower.prob[,3], rev(preds_ideol$upper.prob[,3])), border = NA, col=mygray3)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,1], col="gray20", lwd=2)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,2], col="gray40", lwd=2, lty=2)
lines(preds_ideol$x$IDEOLOGY, preds_ideol$prob[,3], col="black", lwd=2)
text(rep(1,3), c(min(preds_ideol$prob[,1]), min(preds_ideol$prob[,2]),
max(preds_ideol$prob[,3]))+.05, labels = c('Trump', 'Cruz', 'Kasich'))
axis(1, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'Ideology scores',
ylab="Probability of voting",
line = 1.7, cex.lab=1)
title(line = 1, main="Ideology", font.main=3)
dev.off()
|
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