Dear All:

 

I am trying to run 2 Beta-Binomial models using the following code. Everytime I try to run it using R2WinBUGS the trap window opens and stops the process. Is there any way to set R2WinBUGS to ignore the trap window?

Heres my code for running and model code:

library("R2WinBUGS")

#Set working directory
setwd("E://Achaudhuri/Trial")

trial.datatrt <- read.table("simuldatBBtrt_2_63.csv", header=T)
trial.datacont <- read.table("simuldatBBcont_2_63.csv", header=T)
pt_true <- read.table("pt_BBtrt_2_63.csv",header=F)
pc_true <- read.table("pc_BBcont_2_63.csv",header=F)
RR_true <- read.table("RR_true_2_63.csv",header=T)

bugs.output <- list()
for(i in 1:10){
       nauseat <- as.integer(trial.datatrt[i,])
 nauseac <- as.integer(trial.datacont[i,])
       bugs.output[[i]] <- bugs(
       data=list(nauseat=nauseat,nauseac=nauseac,N=63), # change for no of sites
       inits=list(
               list(theta_t=.5,mu_t=6,theta_c=.2,mu_c=6)
              
               ),
       model.file="conj_nausea_script_2_trt.txt",
       parameters.to.save = c("RR","pt","pc"),
n.chains=1, n.iter=12000, n.burnin=5000,
bugs.directory="E://Achaudhuri/winbugs14/WinBUGS14",debug=TRUE,
working.directory=NULL)

bugs.output[[i]]$sims.list$RR_trans<-t(bugs.output[[i]]$sims.list$RR)

bugs.output[[i]]$sims.list$coverage<-matrix(data=0,nrow=63,ncol=1)# Change for no of sites

bugs.output[[i]]$sims.list$int_width<-matrix(data=0,nrow=63,ncol=1)# change for no of sites

bugs.output[[i]]$sims.list$sqr_err<-matrix(data=0,nrow=63,ncol=1)

bugs.output[[i]]$sims.list$abs_bias<-matrix(data=0,nrow=63,ncol=1)# change for no of sites

bugs.output[[i]]$sims.list$RR_true<-RR_true

for (j in 1:63) # change for no of sites

{

if
# define coverage
((bugs.output[[i]]$sims.list$RR_true[j,]>quantile(bugs.output[[i]]$sims.list$RR_trans[j,],c(.025))) & (bugs.output[[i]]$sims.list$RR_true[j,]<quantile(bugs.output[[i]]$sims.list$RR_trans[j,],c(.975))))

bugs.output[[i]]$sims.list$coverage[j,]<-1

else
bugs.output[[i]]$sims.list$coverage[j,]<-0

#define interval width
bugs.output[[i]]$sims.list$int_width[j,]<-(quantile(bugs.output[[i]]$sims.list$RR_trans[j,],c(.975)))-(quantile(bugs.output[[i]]$sims.list$RR_trans[j,],c(.025)))

# define sqr error loss
bugs.output[[i]]$sims.list$sqr_err[j,]<-(((bugs.output[[i]]$sims.list$RR_true[j,])-mean(bugs.output[[i]]$sims.list$RR_trans[j,]))^2)/2 # change with overall relative risk

# define absolute bias
bugs.output[[i]]$sims.list$abs_bias[j,]<-abs((bugs.output[[i]]$sims.list$RR_true[j,])-mean(bugs.output[[i]]$sims.list$RR_trans[j,]))

}

}

cov<-cbind(NULL) # initialize variable matrix cov before loop
interval_width<-cbind(NULL) # initialize variable matrix cov before loop
sqr_error_loss<-cbind(NULL) # initialize variable matrix square error loss
absolute_bias<-cbind(NULL) # initialize variable matrix absolute bias

for(i in 1:10){

cov<-cbind(cov, bugs.output[[i]]$sims.list$coverage)

interval_width<-cbind(interval_width, bugs.output[[i]]$sims.list$int_width)

sqr_error_loss<-cbind(sqr_error_loss, bugs.output[[i]]$sims.list$sqr_err)

absolute_bias<-cbind(absolute_bias, bugs.output[[i]]$sims.list$abs_bias)

}

# Average Coverage
avg_cov<-apply(cov,1,mean)
cov_prob<-mean(avg_cov)
1-cov_prob

# Average Interval Width
avg_int_width<-apply(interval_width,1,mean)
avg_interval_width<-mean(avg_int_width)
avg_interval_width

# Average Square error loss
avg_err_loss<-apply(sqr_error_loss,1,mean)
average_loss<-mean(avg_err_loss)
average_loss

# Average abosulte Bias
avg_abs_bias<-apply(absolute_bias,1,mean)
average_bias<-mean(avg_abs_bias)
average_bias

# Model code

model
{
for (i in 1 : N)

{
nausea_t[i] ~ dbin(pt[i],60)
nausea_c[i] ~ dbin(pc[i],60)

pt[i] ~ dbeta(alpha_t, beta_t)
pc[i] ~ dbeta(alpha_c, beta_c)

RR[i]<-pt/pc
}

alpha_t<-theta_t*mu_t

beta_t<-(1-theta_t)*mu_t

theta_t ~ dbeta(1,1)

mu_t~dpar(1.5,1)

alpha_c<-theta_c*mu_c

beta_c<-(1-theta_c)*mu_c

theta_c ~ dbeta(1,1)

mu_c~dpar(1.5,1)

}

 

Thanks for your help.

Anamika