Multilevel multinomial logistic model with survey weights

[Jascalla]

Hello,
I am running a two-level (multilevel) multinomial (3 categories for the response) logistic regression model using runmlwin in STATA. I tried the models for both second order penalised quasi-likelihood linearization and MCMC which ran correctly without the survey weights as below:

quietly runmlwin outcome cons female, ///
level2(v001x: cons) ///
level1(caseid_1:) ///
discrete(distribution(multinomial) link(mlogit) denominator(cons) ///
basecategory(0)) ///
nopause rrr

/*Second order penalised quasi-likelihood linearization */
runmlwin outcome cons female, ///
level2(v001x: cons) ///
level1(caseid_1:) ///
discrete(distribution(multinomial) link(mlogit) denominator(cons) pql2 ///
basecategory(0)) ///
initsprevious nopause rrr

/* MCMC */
runmlwin outcome cons female, ///
level2(v001x: cons) ///
level1(caseid_1:) ///
discrete(distribution(multinomial) link(mlogit) denominator(cons) ///
basecategory(0)) ///
mcmc(burnin(1000) chain(20000) thinning(2) orthogonal) initsprevious nopause rrr


The challenge: I wish to incorporate survey weights into the Second order penalised quasi-likelihood linearization since this is not possible for MCMC but I got an error saying "Weights are only valid for univariate models estimated using (R)IGLS" after running the code below:

/*Second order penalised quasi-likelihood linearization with survey weight (wt_w=level 2 weights and wt_c=level 1 weights*/
runmlwin outcome cons female, ///
level2(v001x: cons,weightvar(wt_w)) ///
level1(caseid_1:,weightvar(wt_c)) ///
discrete(distribution(multinomial) link(mlogit) denominator(cons) pql2 ///
basecategory(0)) ///
initsprevious nopause rrr

I am using STATA 14.2 and MLwiN v3.05.

Any help will be highly appreciated.

[ChrisCharlton]

Unfortunately, as indicated by the message, you can only specify weights for models that are both fitted with (R)IGLS and have a univariate response via runmlwin.

[Jascalla]

Thank you Chris for confirming this.
Do you have some interest of incorporating this functionality in the near future?
Cheers