Hello,
I'm analyzing the AddHealth data set and was planning to use multiple
imputation to handle the missing data. According to the AddHealth
methodologists they recommend the following Stata syntax to correct for the
complex survey design.
svyset [pweight=gswgt2] , strata(region) psu(psuscid)
svynbreg depvar indvars, subpop(sat_schl)
I've seen a couple messages in the Clarify archives regarding clustering
and weights but I wasn't sure if the same approach would work to account
for everything in the syntax above. In addition to weights, stratification
and clustering, the syntax also uses the "subpop" command to adjust the
standard errors when using a subpopulation. I've run my own analyses
(without multiple imputations) comparing the results using the syntax above
to what I would get if I just did nbreg and used the weights and cluster
commands. The coefficients are pretty much the same and the standard errors
are slightly smaller using svynbreg. Is it ok to just use estsimp nbreg
since Clarify (or MI) can't be used with svynbreg? Are there additional
adjustments I should make if I do so? If you don't recommend using Clarify,
do you know if there are any programs that can be used with the survey
regressions in Stata?
Thanks in advance for any help you can provide.
Kelly
Kelly Richardson
Department of Sociology
W140 Seashore Hall
University of Iowa
Iowa City, IA 52242
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