I am using Stata 16.
I am trying to fit a multilevel model with country random effects on survey data from multiple countries. The response is an unordered categorical variable, so I am using multinomial logit. Here is a sample of my data:
I am treating my data as two-stage: a country gets selected first with a constant probability of 1 (this is a simplifying assumption, since countries were not drawn randomly) and then each response has a final design weight (variable WGT). I also have the strata and PSU id's. So far, my survey design declaration is
The only way to fit a multinomial logit model with random effects to survey data in Stata 16 that I found seems to be through gsem. I am basing it on https://www.stata.com/stata-news/news29-2/xtmlogit/.
This is the model I try to run:
The error message is asking me to specify stage-level weights, which I think in my case are WGT at first stage (individuals) and 1 at second stage (countries). I consulted the Stata manual and did much googling but couldn't figure out how to enter the stage-specific weights, especially a constant 1, into svyset. Does anyone have any ideas?
I am trying to fit a multilevel model with country random effects on survey data from multiple countries. The response is an unordered categorical variable, so I am using multinomial logit. Here is a sample of my data:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input byte(identity age empl sex marstat urban educ) long country double wgt int WP12258 double(WP12258A WP12259) 2 17 5 2 4 3 1 9 0.918483471 1 2017100001 7 1 21 6 2 2 2 2 9 1.063579888 7 2017100007 7 2 22 6 1 2 2 2 9 0.337893372 1 2017100001 10 1 23 6 2 2 2 2 9 1.567769236 18 2017100018 10 1 27 2 1 2 6 1 9 0.475945213 11 2017100011 16 1 28 6 2 2 2 3 9 1.056964223 19 2017100019 16 2 31 1 1 2 2 2 9 0.265830759 7 2017100007 24 2 31 1 2 1 6 1 9 1.072376993 5 2017100005 25 2 32 6 2 3 1 2 9 0.458895125 6 2017100006 33 2 35 6 2 2 3 1 9 1.478014368 1 2017100001 44 1 36 2 1 2 6 1 9 0.43331561 15 2017100015 45 1 37 6 2 1 2 2 9 1.008920356 8 2017100008 53 3 39 1 1 2 2 1 9 0.293730707 1 2017100001 61 1 41 2 1 2 2 2 9 1.298432642 10 2017100010 61 1 41 1 1 2 1 2 9 1.511035436 9 2017100009 80 2 45 2 2 2 1 2 9 0.398746139 1 2017100001 81 1 60 1 1 2 6 1 9 0.553875541 14 2017100014 87 1 60 1 1 1 2 2 9 0.280035342 9 2017100009 91 2 61 2 1 2 2 2 9 2.464917433 5 2017100005 92 1 67 6 1 1 6 1 9 1.056964223 19 2017100019 96 end label values identity WP22091 label def WP22091 1 "Being a part of the city or area where you live", modify label def WP22091 2 "Being a part of this country", modify label def WP22091 3 "Being a part of the world", modify label values age WP1220 label values empl EMP_2010 label def EMP_2010 1 "Employed full time for an employer", modify label def EMP_2010 2 "Employed full time for self", modify label def EMP_2010 5 "Employed part time want full time", modify label def EMP_2010 6 "Out of workforce", modify label values sex WP1219 label def WP1219 1 "Male", modify label def WP1219 2 "Female", modify label values marstat WP1223 label def WP1223 1 "Single/Never been married", modify label def WP1223 2 "Married", modify label def WP1223 3 "Separated", modify label def WP1223 4 "Divorced", modify label values urban WP14 label def WP14 1 "A rural area or on a farm", modify label def WP14 2 "A small town or village", modify label def WP14 3 "A large city", modify label def WP14 6 "A suburb of a large city", modify label values educ WP3117 label def WP3117 1 "Completed elementary education or less (up to 8 years of basic education)", modify label def WP3117 2 "Secondary - 3 year TertiarySecondary education and some education beyond secondary education (9-15 years of educatio", modify label def WP3117 3 "Completed four years of education beyond high school and/or received a 4-year college degree.", modify label values country country label def country 9 "Andorra", modify
Code:
svyset [pweight = wgt], strata(WP12258A) psu(WP12259) singleunit(certainty)
This is the model I try to run:
Code:
. svy: gsem (2.identity <- age i.empl i.sex i.marstat i.urban i.educ R1[country]) (3.identity
> <- age i.empl i.sex i.marstat i.urban i.educ R2[country]), mlogit
(running gsem on estimation sample)
survey final weights not allowed with multilevel models;
a final weight variable was svyset using the [pw=exp] syntax, but multilevel models
require that each stage-level weight variable is svyset using the stage's corresponding
weight() option
an error occurred when svy executed gsem
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