# Data on bills assigned to House committees in the 103rd and 104th Houses of Representatives Data for the committees example used in chapters 6 data ## Format A data frame with 20 rows and 6 variables: - **SIZE**: Number of members on the committee - **SUBS**: Number of subcommittees - **STAFF**: Number of staff assigned to the committee - **PRESTIGE**: Dummy variable indicating whether or not it is a high-prestige committee - **BILLS103**: Number of bills in the 103rd House - **BILLS104**: Number of bills in the 104th House ```r data(committee) ``` ## Examples ```r data(committee) attach(committee) library(AER) library(MASS) library(pscl) ## Table 6.6 committee ## Table 6.7 committee.out <- glm.nb(BILLS104 ~ SIZE + SUBS * (log(STAFF)) + PRESTIGE + BILLS103) summary.glm(committee.out) data.frame(cbind(round(cbind(summary(committee.out)$coef[,1:2], confint(committee.out)),4)[,1], round(cbind(summary(committee.out)$coef[,1:2], confint(committee.out)),4)[,2], round(cbind(summary(committee.out)$coef[,1:2], confint(committee.out)),4)[,3], round(cbind(summary(committee.out)$coef[,1:2], confint(committee.out)),4)[,4])) ## Figure 6.3 z.matrix <- matrix(0,200,200) for(i in 1:200) { for(j in 1:200) { if(j < 70) z.matrix[i,j] <- 1 if(j < 40) z.matrix[i,j] <- 2 if(j < 10) z.matrix[i,j] <- 3 if(j == 1) z.matrix[i,j] <- 3.001 if(j > 130) z.matrix[i,j] <- 1 if(j > 160) z.matrix[i,j] <- 2 if(j > 190) z.matrix[i,j] <- 3 if(j == 200) z.matrix[i,j] <- 3.001 } } pears <- resid(committee.out,type="pearson") devs <- resid(committee.out,type="deviance") x = seq(-2000,2000,length=200) opar = par(mfrow=c(1,1), mar=c(5.1,4.1,4.1,2.1), oma=c(0,0,0,0)) layout(matrix(c(1,2), ncol = 1), heights = c(0.9,0.1)) par(mar=c(3,4,2,4),oma=c(2,2,1,3)) image(seq(0,51,length=200), seq(-2000,2000,length=200),z.matrix,xlim=c(0,51),ylim=c(-2000,2000), xaxt="n",yaxt="n",xlab="",ylab="", col=rev(c("white", "gray40", "gray60", "gray80"))) points(seq(1,50,length=20),(2000/3)*pears[order(BILLS104)],pch=15) lines(seq(1,50,length=20),(2000/3)*devs[order(BILLS104)],type="h") abline(0,0, lwd=2) abline(h=c((x[10]+x[9])/2,(x[40]+x[39])/2,(x[70]+x[69])/2,(x[130]+x[131])/2, (x[160]+x[161])/2,(x[191]+x[190])/2), lty=2) title(xlab = "Order of Fitted Outcome Variable", ylab="Residual Effect", line = 1.3, cex.lab=1.3) title(main="Model Fit Plot", line = 1, cex.main=1.7, font.main=1) par(mar=c(0,1.5,1,1)) plot(0,0, type="n", axes = FALSE, xlab = "", ylab = "") legend("center", ncol = 2, legend = c("Pearson", "Deviances"), cex=1, lty=c(0,1), pch = c(15,NA)) par(opar) ```

committee dataset