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st: how to svyset for stratified multiple-stage cluster sampling in STATA


From   "Jian Zhang" <jzh@ucdavis.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: how to svyset for stratified multiple-stage cluster sampling in STATA
Date   Tue, 18 Apr 2006 11:51:31 -0700 (PDT)

Dear Stata users:

I have a question of how to set up the sampling plan using command svyset 
for stratified multi-stage cluster sampling.  I tried to look for every 
source that I have, but could not figure that out. Hope that you can help 
me out.  Thanks!

Here it is: 

The sample was obtained as follows. I sampled the population by 
stratifying it first, and then I randomly selected several clusters for 
each stratum. Within each cluster, I then random selected several 
subclusters, and then for each subcluster, I randomly selected a certain 
number of observations.  for this sampling plan, how do I set up the 
sampling plan using command svyset in STATA? 
Would it be: 
svyset [pweight = pwt], fpc(fpc) psu(cluster) strata(strata)?

I know this is for stratified TWO-stage cluster sampling plan, which is " 
sample the populitation by strafifying it first, and then randomly select 
several clusters for each stratum. Within each cluster, then randomly 
select a certain number of observations."

Would the svyset for multiple-stage cluster sample (more than  2 stages)
with stratification be same as TWO-stage cluster sampling with 
stratification?

More complicated is that what if I do cluster sampling first, and then 
stratify each cluster, and then do cluster sampling again, what would  
the command svy for settng up this sampling plan be? 

Similarly, if I stratify the populaiton first, and then do the cluster, 
and then do stratification again and then do cluster sampling again, what 
would the svyset command be for this sampling plan?

To generalize the question, if we change the order of cluster sampling 
and stratification sampling when sampling the populaiton, would the 
svyset command be different? 
 
Thank you very much!  
  
Best regards,

Jian Zhang


    
 
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