Nothing
############################################################################
# MLwiN MCMC Manual
#
# 24 Parameter expansion . . . . . . . . . . . . . . . . . . . . . . . .381
#
# Browne, W.J. (2009) MCMC Estimation in MLwiN, v2.13. Centre for
# Multilevel Modelling, University of Bristol.
############################################################################
# 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/
############################################################################
# 24.1 What is Parameter Expansion? . . . . . . . . . . . . . . . . . . .381
# 24.2 The tutorial example . . . . . . . . . . . . . . . . . . . . . . .383
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)
## Read tutorial data
data(tutorial, package = "R2MLwiN")
## Define the model
(mymodel <- runMLwiN(normexam ~ 1 + standlrt + (1 | school) + (1 | student), estoptions = list(EstM = 1), data = tutorial))
summary(mymodel@chains[, "RP2_var_Intercept"])
sixway(mymodel@chains[, "RP2_var_Intercept", drop = FALSE], "sigma2u2")
## Parameter expansion at level 2
(mymodel <- runMLwiN(normexam ~ 1 + standlrt + (1 | school) + (1 | student), estoptions = list(EstM = 1, mcmcOptions = list(paex = c(2,
1))), data = tutorial))
sixway(mymodel@chains[, "RP2_var_Intercept", drop = FALSE], "sigma2u0")
# 24.3 Binary responses - Voting example . . . . . . . . . . . . . . . . 386
## Read bes83 data
data(bes83, package = "R2MLwiN")
## Define the model
(mymodel <- runMLwiN(logit(votecons) ~ 1 + defence + unemp + taxes + privat + (1 | area), D = "Binomial", estoptions = list(EstM = 1),
data = bes83))
sixway(mymodel@chains[, "RP2_var_Intercept", drop = FALSE], acf.maxlag = 500, "sigma2u0")
## Parameter expansion at level 2
(mymodel <- runMLwiN(logit(votecons) ~ 1 + defence + unemp + taxes + privat + (1 | area), D = "Binomial", estoptions = list(EstM = 1,
mcmcOptions = list(paex = c(2, 1))), data = bes83))
sixway(mymodel@chains[, "RP2_var_Intercept", drop = FALSE], acf.maxlag = 500, "sigma2u0")
# 24.4 The choice of prior distribution . . . . . . . . . . . . . . . . .390
## Uniform on the variance scale priors+Parameter expansion at level 2
(mymodel <- runMLwiN(logit(votecons) ~ 1 + defence + unemp + taxes + privat + (1 | area), D = "Binomial", estoptions = list(EstM = 1,
mcmcMeth = list(priorcode = 0), mcmcOptions = list(paex = c(2, 1))), data = bes83))
sixway(mymodel@chains[, "RP2_var_Intercept", drop = FALSE], acf.maxlag = 100, "sigma2u0")
# 24.5 Parameter expansion and WinBUGS . . . . . . . . . . . . . . . . . 391
mymodel <- runMLwiN(logit(votecons) ~ 1 + defence + unemp + taxes + privat + (1 | area), D = "Binomial", estoptions = list(EstM = 1,
mcmcMeth = list(priorcode = 0), mcmcOptions = list(paex = c(2, 1)), show.file = TRUE), BUGO = c(version = 4, n.chains = 1,
debug = FALSE, seed = 1, OpenBugs = TRUE), data = bes83)
summary(mymodel)
if (!require(coda)) {
warning("package coda required to run this example")
} else {
effectiveSize(mymodel)
}
sixway(mymodel[, "sigma2.u2", drop = FALSE], acf.maxlag = 250)
sixway(mymodel[, "sigma2.v2", drop = FALSE], acf.maxlag = 100)
# 24.6 Parameter expansion and random slopes . . . . . . . . . . . . . . 396
## Read tutorial data
data(tutorial, package = "R2MLwiN")
## Define the model
(mymodel <- runMLwiN(normexam ~ 1 + standlrt + (1 + standlrt | school) + (1 | student), estoptions = list(EstM = 1),
data = tutorial))
## Parameter expansion at level 2
(mymodel <- runMLwiN(normexam ~ 1 + standlrt + (1 + standlrt | school) + (1 | student), estoptions = list(EstM = 1,
mcmcOptions = list(paex = c(2, 1))), data = tutorial))
# Chapter learning outcomes . . . . . . . . . . . . . . . . . . . . . . .399
############################################################################
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.