Hi~
I would appreciate any suggestions about how I might estimate a three-level model that adjusts for clustering at two levels (relationship-within-individual and individual-within-school). Can this be done using GLLAMM (or any other way)?
I am trying to estimate a regression model using relationship-level data that I created from individual-level data. When analyzing individual-level data, the correct survey command for the waves of data that I am using is:
svyset [pweight=pw1], strata(st) psu(psu)
But I am analyzing relationship-level data in which a respondent might contribute several observations (if s/he reported several relationships) or no observations (if s/he reported no relationships), so I also need to cluster by respondent.
I have tried the following command in GLLAMM:
gllamm ...., i(id psu st) pweight(pw) link(logit) family(bin)
Where id = respondent ID
Is this correctly specified? And is there any way to increase the speed of estimation? I have 3 dependent variables and for one of these outcomes the estimation process seems to be iterating interminably (over a week so far...). I tried adding the option "nip(4)" but this did not seem to help much. The sample size is about 20,000.
Thank you in advance for any advice you can give me!
~Elizabeth
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