--- "Daniel Schneider" <daniel.schneider@s...> wrote:
> I ran a score test (with the omodel routine) and the result was a
> bit discouraging as the Prob > chi2 constantly stayed below .05
> whatever I did with the modell.
>
> After I tried several other things like gologit (which is also a bit
> troublesome because of some other assumptions and the fact that in
> my view it is even harder to make interpretations), creating an
> index for the same DV with some other variables and then running
> OLS (which didn't work because the residuals still had some
> problems, like non-normality and heteroscedasticity).
>
> So, I am left wondering with what else to do and especially the
> question how seriously I have to take the score test. I have a
> sample size with n=1.500, and I was wondering if that might affect
> the p-level of the test.
>
-omodel- test the proportional odds assumption that underlies the
orderd logit model. This assumption is often violated. You could use
the -brant- command (part of spost) after -ologit- to see which
variable(s) cause problems and enforce the proportional odds
assumption for the uproblematic variables in gologit by applying
constraints to get a more parsimonious (interpretable) model.
Alternatively, you could estimate a multinomial logit (which relaxes
the proportional odds assumption for all variables).
Hope this helps,
Maarten
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