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# MLwiN MCMC Manual
#
# 11 Poisson Response Modelling . . . . . . . . . . . . . . . . . . . . 153
#
# Browne, W.J. (2009) MCMC Estimation in MLwiN, v2.13. Centre for
# Multilevel Modelling, University of Bristol.
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# R script to replicate all analyses using R2MLwiN
#
# Zhang, Z., Charlton, C., Parker, R, Leckie, G., and Browne, W.J.
# Centre for Multilevel Modelling, 2012
# http://www.bristol.ac.uk/cmm/software/R2MLwiN/
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library(R2MLwiN)
# MLwiN folder
mlwin <- getOption("MLwiN_path")
while (!file.access(mlwin, mode = 1) == 0) {
cat("Please specify the root MLwiN folder or the full path to the MLwiN executable:\n")
mlwin <- scan(what = character(0), sep = "\n")
mlwin <- gsub("\\", "/", mlwin, fixed = TRUE)
}
options(MLwiN_path = mlwin)
# User's input if necessary
## Read mmmec data
data(mmmec, package = "R2MLwiN")
# 11.1 Simple Poisson regression model . . . . . . . . . . . . . . . . . 155
(mymodel1 <- runMLwiN(log(obs) ~ 1 + uvbi + offset(log(exp)), D = "Poisson", estoptions = list(EstM = 1, mcmcMeth = list(iterations = 50000)),
data = mmmec))
summary(mymodel1@chains[, "FP_uvbi"])
sixway(mymodel1@chains[, "FP_uvbi", drop = FALSE], "beta_1")
# 11.2 Adding in region level random effects . . . . . . . . . . . . . . 157
(mymodel2 <- runMLwiN(log(obs) ~ 1 + uvbi + offset(log(exp)) + (1 | region), D = "Poisson", estoptions = list(EstM = 1,
mcmcMeth = list(iterations = 50000, seed = 13)), data = mmmec))
summary(mymodel2@chains[, "FP_uvbi"])
sixway(mymodel2@chains[, "FP_uvbi", drop = FALSE], "beta_1")
# 11.3 Including nation effects in the model . . . . . . . . . . . . . . 159
(mymodel3 <- runMLwiN(log(obs) ~ 1 + uvbi + offset(log(exp)) + (1 | nation) + (1 | region), D = "Poisson", estoptions = list(EstM = 1,
mcmcMeth = list(iterations = 50000, seed = 13)), data = mmmec))
(mymodel4 <- runMLwiN(log(obs) ~ 0 + uvbi + nation + offset(log(exp)) + (1 | region), D = "Poisson", estoptions = list(EstM = 1,
mcmcMeth = list(iterations = 50000)), data = mmmec))
# 11.4 Interaction with UV exposure . . . . . . . . . . . . . . . . . . .161
(mymodel5 <- runMLwiN(log(obs) ~ 0 + nation + nation:uvbi + offset(log(exp)) + (1 | region), D = "Poisson", estoptions = list(EstM = 1,
mcmcMeth = list(iterations = 50000)), data = mmmec))
sixway(mymodel5@chains[, "FP_nationBelgium", drop = FALSE], acf.maxlag = 5000, "beta_1")
# 11.5 Problems with univariate updating Metropolis procedures . . . . . 163
(mymodel6 <- runMLwiN(log(obs) ~ 0 + nation + nation:uvbi + offset(log(exp)) + (1 | region), D = "Poisson", estoptions = list(EstM = 1,
mcmcMeth = list(iterations = 500000, thinning = 10)), data = mmmec))
sixway(mymodel6@chains[, "FP_nationBelgium", drop = FALSE], "beta_1")
# Chapter learning outcomes . . . . . . . . . . . . . . . . . . . . . . .128
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