suicide {GLMpack} | R Documentation |
Data on suicides in 2009 in OECD member states
Description
Data for the suicide example used in chapter 7
Usage
data(suicide)
Format
A data frame with 32 rows and 7 variables:
- COUNTRYCODE
Country code
- COUNTRYNAME
Name of the country
- YEAR
Year
- DEATHS
Number of suicides in the country per 100,000 individuals
- GDP
GDP in thousands of dollars
- SUBABUSE
Share of the population with alcohol or drug use disorder
- TEMP
Average temperature
...
Examples
opar = par(mfrow=c(1,1), mar=c(5.1,4.1,4.1,2.1), oma=c(0,0,0,0))
data(suicide)
attach(suicide)
## Table 7.2
# Poisson model
suic.out.p <- glm(DEATHS ~ GDP + TEMP + SUBABUSE, family = poisson)
summary(suic.out.p)
round(confint(suic.out.p),3)
coefs_poisson <- summary(suic.out.p)$coefficients[1:4,]
coefs_poisson
suic.out.qp <- glm(DEATHS ~ GDP + TEMP + SUBABUSE, family = quasipoisson)
summary(suic.out.qp)
round(confint(suic.out.qp),3)
coefs_quasipoisson <- summary(suic.out.qp)$coefficients[1:4,]
coefs_quasipoisson
## Figure 7.1
layout(matrix(c(1,2,3,4), ncol=2, byrow = TRUE))
par(mar=c(4,3,2,0),oma=c(1,1,1,1))
# Histogram #1
hist(TEMP,xlab="",ylab="", yaxt="n", xaxt="n", main="", col="gray50", border = "gray30",
ylim=c(0,15))
axis(1, tck=0, mgp=c(0, 0, 0), lty=1, lwd=0, lwd.ticks = 0)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=1, lwd.ticks = 1, las=2)
title(xlab = 'Mean temperature (in Celsius)', ylab="",
line = 1.7, cex.lab=1.2)
title(line = 1, main="Temperature", font.main=3)
# Histogram #2
hist(GDP,xlab="",ylab="", yaxt="n", xaxt="n", main="", col="gray50", border = "gray30",
ylim=c(0,15))
axis(1, tck=0, mgp=c(0, 0, 0), lty=1, lwd=0, lwd.ticks = 0)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=1, lwd.ticks = 1, las=2)
title(xlab = 'GDP per capita (in thousands of dollars)', ylab="",
line = 1.7, cex.lab=1.2)
title(line = 1, main="Economic Conditions", font.main=3)
# Histogram #3
hist(SUBABUSE,xlab="",ylab="", yaxt="n", xaxt="n", main="", col="gray50", border = "gray30",
ylim=c(0,15))
axis(1, tck=0, mgp=c(0, 0, 0), lty=1, lwd=0, lwd.ticks = 0)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=1, lwd.ticks = 1, las=2)
title(xlab = '% of population with alcohol or drug use disorders', ylab="",line = 1.7, cex.lab=1.2)
title(line = 1, main="Substance abuse", font.main=3)
# Histogram #4
hist(DEATHS,xlab="",ylab="", yaxt="n", xaxt="n", main="", col="gray10", border = "gray20",
ylim=c(0,15))
axis(1, tck=0, mgp=c(0, 0, 0), lty=1, lwd=0, lwd.ticks = 0)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=1, lwd.ticks = 1, las=2)
title(xlab = 'Number of suicides per 100,000 people', ylab="",
line = 1.7, cex.lab=1.2)
title(line = 1, main="Suicide rate", font.main=3)
par(opar)
## Figure 7.2
newdat1 <- data.frame(GDP=seq(13, 70.5, 1), TEMP=rep(mean(TEMP), 58),
SUBABUSE=rep(mean(SUBABUSE), 58))
newdat2 <- data.frame(GDP=rep(mean(GDP), 61), TEMP=rep(mean(TEMP), 61), SUBABUSE=seq(0,6,0.1))
preds.qp.gdp <- predict(suic.out.qp, newdata = newdat1, type = "link", se.fit = TRUE)
preds.qp.subabuse <- predict(suic.out.qp, newdata = newdat2, type = "link", se.fit = TRUE)
ilink.qp <- family(suic.out.qp)$linkinv
cis.p.preds.qp.gdp <- cbind(ilink.qp(preds.qp.gdp$fit - (2 * preds.qp.gdp$se.fit)),
ilink.qp(preds.qp.gdp$fit + (2 * preds.qp.gdp$se.fit)))
cis.p.preds.qp.subabuse <- cbind(ilink.qp(preds.qp.subabuse$fit - (2 * preds.qp.subabuse$se.fit)),
ilink.qp(preds.qp.subabuse$fit + (2 * preds.qp.subabuse$se.fit)))
mygray = rgb(153, 153, 153, alpha = 200, maxColorValue = 255)
par(mar=c(4,3,1,0),oma=c(1,1,1,1), mfrow=c(1,2))
plot(newdat1$GDP, ilink.qp(preds.qp.gdp$fit), type="n",xlab="",ylab="", yaxt="n", xaxt="n", lwd=2,
ylim = c(0,37))
polygon(c(newdat1$GDP,rev(newdat1$GDP)), c(cis.p.preds.qp.gdp[,1],rev(cis.p.preds.qp.gdp[,2])),
border = NA, col = mygray)
lines(newdat1$GDP, ilink.qp(preds.qp.gdp$fit))
points(GDP, DEATHS, pch="+", col="gray20", cex=0.8)
axis(1, tck=0.03, cex.axis=0.9, at=seq(20,70,10), labels = seq(20,70,10), mgp=c(0.3, 0.3, 0),
lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'GDP per capita (in thousands of dollars)',
ylab="Number of suicides per 100,000 people", line = 1.7, cex.lab=1.2)
plot(newdat2$SUBABUSE, ilink.qp(preds.qp.subabuse$fit), type="n",xlab="",ylab="",
yaxt="n", xaxt="n", lwd=2, ylim = c(0,37))
polygon(c(newdat2$SUBABUSE,rev(newdat2$SUBABUSE)), c(cis.p.preds.qp.subabuse[,1],
rev(cis.p.preds.qp.subabuse[,2])), border = NA, col = mygray)
lines(newdat2$SUBABUSE, ilink.qp(preds.qp.subabuse$fit))
points(SUBABUSE, DEATHS, pch="+", col="gray20", cex=0.8)
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 = '% of population with alcohol or drug use disorders', ylab="",
line = 1.7, cex.lab=1.2)
par(opar)
[Package GLMpack version 0.1.0 Index]