Dear Statalists,

I am new here in the forum.

I have worked on a model for some time, and I am quite concerned whether I have done it right and in addition I have some questions to interpretation - I hope someone has the time to help. It would mean a lot.

My dv is support for democracy: 0 - not supportive and 1 - supportive.
As a first step I am interested in whether gdp annual growth has an effect on support for democracy.

My data are survey data from 18 countries with each 1200 obs. from 20 years, so approx. 400.000 obs. in total.
My gdp data are aprox. 400 obs (from each year in each country) merged with the other 20 datasets.

I have made the null-model/baseline-model:

meqrlogit SforD time|| country1:time, cov(indep)

and a random intercept model:

meqrlogit SforD gdp_lag2 time|| country1:time, cov(indep)

and a random slope model:

meqrlogit SforD gdp_lag2 time|| country1:time gdp_lag2,


I only have 18 countries, but with the time dimension, I have 400 gdp growth observations, I am just not sure if time is placed right in the model? and if the model even is the right one, when I have the time dimension?

My gdp growth is not significant when I include the random slope, but I have read that with only 18 level 2 variables, I might not have sufficient statistical power to run the model. (I just assumed that I could have countries*years or something?). Would it be ok to just run a model of random intercept? and leave out the random slope model? (when I don't know if it is actually a statistical issue at stake).

My general question is, when dealing with 1) binary outcome 2) a level-2 independent variable 3) TSCS data - have I reached the right model, or is there any other obvious solution? + How does the syntax look to you?

In addition, I am a bit concerned about how to interpret the odds ratios, as I have read that it might be biased due to the random effect part. In that case, can I only report the significance level and direction or is there a way I can get unbiased odds ratios or otherwise report my model?

Best regards,
Tammie Schwartz