Hi Statalist,

I would like to estimate a complementary loglog model with induvidual effects using Stata's xtcloglog command.

My dependent variabel is binary with rare events and I have a panel structure with small T and large N, so everything is fine for this kind of model.

I am now struggeling whether to use the pa (population averaged) or re (random effects) option for accounting for individual effects.
The general differences of thes two models are described e.g. here:
https://www.stata.com/support/faqs/s...tion-averaged/
and in more detail here:
http://journals.sfu.ca/llcs/index.ph...ewFile/249/238

The problem ist that I am interested in the marginal effects of a count variable (number of patents applied) on the dependent variable (the probability of bankruptcy of a firm) and that the results are very different for the pa and re model.
The second source I posted says (on page 155-156) that because of the non-llinearity of the assumed distribution the estimated coefficients differ and how they differ. However they also say that standard errors should vary proportionally and thus no serious effects on significant tests are to be expected. But in my case only one model delivers statistical significant results.
I estimate the marginal effects using the margins command at different values of my explanatory variable (say 0, 1 or 5 patents) and the atmeans option for the controls. I suppose no more information about my data is needed to understand the problem but I can offer later.

So beside the effects that it is obviously relevant to select the correct option (re or pa) for the research question, why do the marginal effects for point-estimates and standard errors differ quite substatially?

Thanks and best regards

Tim