Dear Spencer,
Many-thanks for responding to my question.
Below, I have set out an example to illustrate my question.
Example, consider the jth data set called 'EXAMPLE.j' as follows:
group family y1 y2
1 1 2.3 3.4
1 1 3.4 --
1 1 1.5 2.3
1 2 -- 2.4
1 2 2.4 3.4
1 2 -- 1.2
0 1 2.1 --
0 1 -- 4.5
0 1 3.5 2.5
0 2 3.4 --
0 2 4.4 3.4
0 2 2.2 2.1
The standard s-codes for Multiple Imputation are as follows:
start <- list()
for(i in 1:5)
start[[i]] <- paramIter(emGauss(EXAMPLE.j,
subset=sample(1:12,6,T), prior="ml")) # draw 5 imputations from 5 parallel
chains
EXAMPLE.imp <- impGauss(EXAMPLE.j, prior="non", start=start,
control=list(niter=50)) # Run for 50 iterations
Now imagine I have 1000 of similar data sets in a loop as follows:
For (j in 1:1000){
start <- list()
for(i in 1:5)
start[[i]] <- paramIter(emGauss(EXAMPLE.j,
subset=sample(1:12,6,T), prior="ml")) # draw 5 imputations from 5 parallel
chains
EXAMPLE.imp <- impGauss(EXAMPLE.j, prior="non", start=start,
control=list(niter=50)) # Run for 50 iterations
}
The problem lies in creating starting values/imputation sets for each j data
set. I would eventually get non-convergence for a set of imputations i.e.
the imputation would go forever and the loop would not stop. I have tried
several sub-loops but that didn't help.
I hope the above example helps.
Many-thanks,
Ken Nip
-----Original Message-----
From: Spencer Graves [mailto:spencer.graves@PDF.COM]
Sent: 22 April 2003 21:38
To: Ken Nip
Cc: 's-news@lists.biostat.wustl.edu'
Subject: Re: [S] Multiple Imputations within a loop
1. Have you considered "try"?
2. If you provide a simple example that illustrates the problem, it is
easier for others to help.
spencer graves
Ken Nip wrote:
> The data set that I am looking at consists of thousands
> of n.samples-by-p.variables multivariate data sets containing missing
> data. For each data set I would like to impute missing data using DA
> method, so I've decided to explore and use a loop. Unfortunately, I am
> having not much of a success with DA within a large 'for' loop. I am
> having convergence problem for the starting values (created by either
> bootstrap or parallel chains) at some point within the loop. I have
> checked that it wasn't the case when I manually run DA on the data sets
> which caused the non-convergence. I wonder whether I shouldn't use DA
> within a loop at all or is there something else I should be made aware
> off. Has anyone came across with a similar problem before? Any
> recommendations would be great.
>
> Thanks in advance.
>
> Ken Nip
>
>
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