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From | Richard Williams <richardwilliams.ndu@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: gologit2 model |
Date | Wed, 13 Oct 2010 15:35:46 -0500 |
At 01:10 PM 10/13/2010, Nilam Prasai wrote:
Thanks Martin and Richard. Just to make my problem clear. I have all independent variable either categorical or dummy except one. Can it leads to negative probability as my model do not include any continuous variable. Furthermore, what would be the good sample size to run maximul likelihood estimates (how would I know if a small sample size is causing problem to my model).
You are getting negative predicted probabilities, so apparently it is possible! As for sample size, the rule seems to be that you should have at least 100 cases for ML analyses, and that is for relatively simple models. I'd probably want several hundred cases for models like mlogit and gologit, and/or a model with very few independent variables.
A revision to my problem: I am trying to estimate a generalized ordinal logistic model by using gologit2 program in stata. I have approximately 40 observations for which predicted probability is negative. Should I be concerned. My sample size is 115.
I've seen analyses with several thousand cases, and maybe 0 to 3 had negative predicted probabilities. 40 out of 115 is extremely high. Are you sure you even need gologit2? With a sample that small, even if assumptions are violated, the violations may not be statistically significant. Again, see the FAQ. You may need to combine categories, drop variables, or choose a different method altogether.
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