@ND - lab:projects:12bayesian_random_coefficients_lcsm
https://nd.psychstat.org/
2026-05-05T11:24:25+00:00@ND
https://nd.psychstat.org/
https://nd.psychstat.org/_media/wiki/dokuwiki.svgtext/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)alternative_specification
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/alternative_specification
model{
for (i in 1:N){
LS[i, 1]~dnorm(mu[1], inv_sigL2)
LS[i, 2]~dnorm(muS[i], inv_sigS2)
muS[i]<-mu[2]+lambda*(LS[i,1]-mean(LS[,1]))
Y[i,1]~dnorm(y[i,1],inv_sig_e2)
y[i,1]<-LS[i,1]
for (t in 2:T){
Y[i,t]~dnorm(y[i,t], inv_sig_e2)
d[i,t-1]<-gamma[i,t-1]*y[i,t-1]+LS[i,2]
y[i,t]<-d[i,t-1]+y[i,t-1]
## another way to deal this
gamma[i, t-1]~dnorm(mugamma[i,t-1], inv_sig_v2)
mugamma[i, t-1]…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)another_way
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/another_way
model{
for (i in 1:N){
R[i, 1] ~ dnorm(0,1)
R[i, 2] ~ dnorm(0, 1)
LS[i, 1]<-mu[1]+sigma[1]*R[i,1]
LS[i, 2]<-mu[2]+rho*sigma[2]*R[i,1]+sigma[2]*sqrt(1-rho*rho)*R[i,2]
Y[i,1]~dnorm(y[i,1],inv_sig_e2)
y[i,1]<-LS[i,1]
for (t in 2:T){
Y[i,t]~dnorm(y[i,t], inv_sig_e2)
d[i,t-1]<-gamma[i,t-1]*y[i,t-1]+LS[i,2]
y[i,t]<-d[i,t-1]+y[i,t-1]
## another way to deal this
gamma[i, t-1]~dnorm(mugamma[i,t-1]…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)bugs_codes_for_the_model_random_-_ranmodel.txt
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/bugs_codes_for_the_model_random_-_ranmodel.txt
model{
for (i in 1:N){
LS[i,1:2]~dmnorm(mu[1:2], inv_sig_LS[1:2,1:2])
Y[i,1]~dnorm(y[i,1],inv_sig_e2)
y[i,1]<-LS[i,1]
for (t in 2:T){
Y[i,t]~dnorm(y[i,t], inv_sig_e2)
d[i,t-1]<-gamma[i,t-1]*y[i,t-1]+LS[i,2]
y[i,t]<-d[i,t-1]+y[i,t-1]
## another way to deal this
gamma[i, t-1]~dnorm(mugamma[i,t-1], inv_sig_v2)
mugamma[i, t-1]<-beta0+beta1*X[i,t-1] + beta2*Z[i]
}
}
inv_sig_e2~dgamma(.001,.00…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)data_generation
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/data_generation
* Using Bugs
##Model part
model{
for (i in 1:N){
LS[i,1:2]~dmnorm(mu[1:2], inv_sig_LS[1:2,1:2])
Y[i,1]~dnorm(y[i,1],inv_sig_e2)
y[i,1]<-LS[i,1]
for (t in 2:T){
Y[i,t]~dnorm(y[i,t], inv_sig_e2)
d[i,t-1]<-gamma[i,t-1]*y[i,t-1]+LS[i,2]
y[i,t]<-d[i,t-1]+y[i,t-1]
## another way to deal this
gamma[i, t-1]~dnorm(mugamma[i,t-1], inv_sig_v2)
mugamma[i, t-1]<-beta1*X[i,t-1] + beta2*Z[i]
X[i,t-1]~dnorm(0,1)
…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)generate_simulation_scripts
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/generate_simulation_scripts
Process the results
geweke<-function(x, frac1 = 0.2, frac2 = 0.5){
xstart <- c(start(x), end(x) - frac2 * (end(x) - start(x)))[c(1,3)]
xend <- c(start(x) + frac1 * (end(x) - start(x)), end(x))[c(1,3)]
y.variance <- y.mean <- vector("list", 2)
for (i in 1:2) {
y <- window(x, start = xstart[i], end = xend[i])
y.mean[[i]] <- apply(as.matrix(y), 2, mean)
y.variance[[i]] <- apply(as.matrix(y), 2, var)
}
z <- (y.mean[[1]] - y.mean[[2]])/sqrt(y.variance[[1…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)index
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/index
Random coefficients LCSM
NLSY97 data
* [Data set]
* Variables in the data set
* Outcome: piat1-piat5: PIAT math test standard score from Year 1998-2002
* Time varying covariates: smoke1-smoke5: # of days smoked in last 30 days Year 1998-2002
* Time invariant covariates: op: optimistic about the future (1997), depress: depression at 2002text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)initial_value_file_-_raninits.txt
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/initial_value_file_-_raninits.txt
list(beta0=-.3, beta1=0,beta2=0,inv_sig_e2=1,inv_sig_v2=.1, mu=c(3,10), inv_sig_LS=structure(.Data=c(1,0,0,1),.Dim=c(2,2)))text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)r_codes_to_run_the_simulation
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/r_codes_to_run_the_simulation
for (r in 1:1000){
## copy data
from.file<-paste('/pscratch/zzhang4/Private/LCSM/data/simdata-N',NSIM,'-T',TSIM,'-',r,'.txt', sep='')
to.file<-paste('/pscratch/zzhang4/Private/LCSM/analysis/N',NSIM,'T',TSIM,'/data.txt', sep='')
file.copy(from.file, to.file,overwrite =TRUE)
runtry<-try(system('/pscratch/zzhang4/Private/bugs/bin/OpenBUGS < script.txt > out.txt'))
if (class(runtry) != "try-error"){
## save the output
## copy the DIC
to.file<-paste('/pscratch/zzhang4/Private…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)script_file_-_ranscript.txt
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/script_file_-_ranscript.txt
modelCheck("model.txt")
modelData("data.txt")
modelCompile()
modelInits("inits.txt")
modelGenInits()
modelUpdate(10000)
samplesSet("para")
modelPrecision(8)
dicSet()
modelUpdate(50000)
dicStats();
samplesCoda("para","coda")
modelQuit()text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)submission_file_-_ransub.sh
https://nd.psychstat.org/lab/projects/12bayesian_random_coefficients_lcsm/submission_file_-_ransub.sh
#!/bin/csh
#$ -M zzhang4@nd.edu
#$ -m abe
#$ -r y
module load R
R CMD BATCH runsim.R