BookCodes/Ch25/25.5.R

In dsy109/HoRM: Supplemental Functions and Datasets for "Handbook of Regression Methods"

library(ggplot2)
library(MASS)
library(lattice)
library(HLMdiag)
library(fda)
library(rgl)
library(DepthProc)
library(alr3)
library(NPCirc)
library(quantreg)
library(mixtools)
library(Rfit)
library(extRemes)
library(ismev)
library(spdep)
library(multilevel)
library(survey)
library(SDaA)
library(bayesm)
library(coda)
library(ggmcmc)
library(SemiPar)
library(gcmr)
library(MAd)
library(metafor)
library(VIM)
library(astsa)
library(rTensor)
library(tensorA)
library(dplyr)
library(RandomFields)
library(lme4)

###############################################################################
### Example 25.5.1: Tuberculosis Vaccine Literature Data
###############################################################################

data(dat.bcg, package = "metafor")
bcg <- escalc(measure = "RR", ai = tpos, bi = tneg, ci = cpos, di = cneg, data = dat.bcg)
fe.fit <- mareg(yi ~ alloc, var = vi, method = "FE", data = bcg)
summary(fe.fit)
re.fit <- mareg(yi ~ year + ablat, var = vi, method = "REML", data = bcg)
summary(re.fit)

df7 <- data.frame(x = exp(c(bcg$yi)), y = exp(predict(fe.fit)$pred), Group = c(rep("Random", 
    4), rep("Alternate", 2), rep("Random", 3), rep("Systematic", 4)))
df7$Group <- as.factor(df7$Group)
ggplot(data = df7, aes(x = x, y = y, col = Group, shape = Group)) + geom_point(size = 4) + 
    theme(text = element_text(size = 20)) + ggtitle("Fixed-Effect Meta-Regression Fits") + 
    xlab("Relative Risk") + ylab("Predicted Relative Risk")

df8 <- data.frame(x = exp(c(bcg$yi)), y = exp(predict(re.fit)$pred), Group = c(rep("Random", 
    4), rep("Alternate", 2), rep("Random", 3), rep("Systematic", 4)))
ggplot(data = df8, aes(x = x, y = y, col = Group, shape = Group)) + geom_point(size = 4) + 
    ggtitle("Random-Effects Meta-Regression Fits") + xlab("Relative Risk") + ylab("Predicted Relative Risk") + 
    theme(text = element_text(size = 20))