@ND - lab:projects:03growth_curve_modeling_with_mnar_data
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2026-04-21T18:33:00+00:00@ND
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https://nd.psychstat.org/_media/wiki/dokuwiki.svgtext/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)a_simulated_example_single_replication
https://nd.psychstat.org/lab/projects/03growth_curve_modeling_with_mnar_data/a_simulated_example_single_replication
Model{
# Model specification for linear growth curve model
for (i in 1:N){
LS[i,1:2]~dmnorm(muLS[i,1:2], Inv_cov[1:2,1:2])
muLS[i,1]<-bL[1]
muLS[i,2]<-bS[1]
for (t in 1:5){
y[i, t] ~ dnorm(muY[i,t], Inv_Sig_e2)
muY[i,t]<-LS[i,1]+LS[i,2]*t
## missing data mechanism
m[i,t]~dbern(p[i,t])
p[i,t]<-phi(gam[t,1]+gam[t,2]*LS[i,1]+gam[t,3]*LS[i,2])
}
}
#Priors for model parameter
for (i in 1:1){
bL[i] ~ dnorm(0, 1.0E-6)
bS[i] ~ dnorm(0…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)index
https://nd.psychstat.org/lab/projects/03growth_curve_modeling_with_mnar_data/index
Growth curve modeling with MNAR data
Manuscripts
* Version 1.
References
* [MNAR data for a regression model]
Results
Scripts/codes
* MNAR data generation
* A simulated example (single replication)
* Using Mplus [Input file] [Data]
An working example
#WinBUGS codes generated by BAUW: http://bauw.psychstat.org
#USE WITH CAUTION!
Model{
# Model specification for linear growth curve model
for (i in 1:N){
LS[i,1:2]~dmnorm(muLS[i,1:2], Inv_cov[1:2,1:2])
muLS[i,1]<-bL…text/html2016-01-24T14:48:26+00:00Anonymous (anonymous@undisclosed.example.com)mnar_data_generation
https://nd.psychstat.org/lab/projects/03growth_curve_modeling_with_mnar_data/mnar_data_generation
library(mvtnorm)
source('/Users/zzhang4/zzy/Classes/Applied\ Bayesian\ Methods/Spring2010/rtobugs.r')
grm.linear<-function(N, T, R){
## Constants and parameters
mL<-60
vL<-200
mS<-3
vS<-3
vLS<-0
vE<-100
mu<-c(mL,mS)
sigma<-array(c(vL,vLS,vLS,vS), dim=c(2,2))
y<-array(NA, dim=c(N, T))
LS<-array(NA, dim=c(N, 2))
p<-array(NA, dim=c(N, T))
for (i in 1:N){
LS[i,]<-rmvnorm(1, mu, sigma)
for (j in 1:T){
y[i, j] <- LS[i,1] + LS[i,2]*(j-1) + rnorm(1, 0, sqrt(vE))
p[i, j] <- pnorm(-2 + LS[…