I am not sure how you are doing this but there is a package on CRAN which implements the Copas model (metasens). I am not sure whether that would help in your modelling.

On 01/08/2015 02:36, Christopher Kelvin via R-help wrote:
Dear All,
I am performing some simulations for a new model. I run about 10,000 iterations 
with a sample of 50 datasets and this returns one set of 50 simulated data.

Now, what I need to obtain is 10 sets of the 50 simulated data out of the 
10,000 iterations and not just only 1 set.  The model is the Copas selection 
model for publication bias in Mete-analysis. Any one who knows this model has 
any suggestion for the improvement of my code is most welcome.

Below is my code.


Kind regards


Chris Guure
University of Ghana




install.packages("msm")
library(msm)


rho1=-0.3; tua=0.020; n=50; d=-0.2; rr=10000; a=-1.3; b=0.06
si<-rtnorm(n, mean=0, sd=1, lower=0, upper=0.2)# I used this to generate 
standard errors for each study
set.seed(21111)   ## I have stored the data and the output in this seed

for( i in 1:rr){

mu<-rnorm(n,d,tua^2)              # prob. of each effect estimate
rho<-si*rho1/sqrt(tua^2 + si^2) # estimate of the correlation coefficient
mu0<- a + b/si       # mean of the truncated normal model (Copas selection 
model)
y1<-rnorm(mu,si^2)            # observed effects zise
z<-rnorm(mu0,1)               # selection model
rho2<-cor(y1, z)

select<-pnorm((mu0 + rho*(y1-mu)/sqrt(tua^2 + si^2))/sqrt(1-rho^2))
probselect<-ifelse(select<z, y1, NA)# the prob that the study is selected

probselect
data<-data.frame(probselect,si)    # this contains both include and exclude data
data
data1<-data[complete.cases(data),] # Contains only the included data for 
analysis
data1


}

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--
Michael
http://www.dewey.myzen.co.uk/home.html

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