"omodel is an alternative to ologit and oprobit for estimating ordered
logit and probit models. It produces the same results but it also reports an
approximate likelihood-ratio test of whether the coefficients are equal across
categories (i.e. a test of the proportional-odds assumption if logit is the
requested model). "
-mlogtest- is another post-estimation command that computes a variety of tests
for multinomial logit models that you might find useful.
hope this helps,
Scott
----- Original Message -----
From: "jaswartz" <[email protected]>
To: <[email protected]>
Sent: Sunday, January 11, 2004 5:07 PM
Subject: st: Testing predictor coefficients in ordinal logistic regression
> All,
>
> As I understand ordered logistic regression, the predictor coefficients (and
> odds ratios) are based on the assumption that the pedictor variable has the
> same effect (slope) across all categories of the dependendent variable. In the
> models I am working with, I do not believe this is a tenable assumption. In
> fact, one of my hypotheses is that serious mental illness has a larger effect
> in moving a person from drug use to dependence on that drug (categories 2 and
> 3 for the dependent variable - drug use/dependence) than it does on moving
> people from no use to use (categories 1 and 2). For this reason, I have been
> using multinomial logistic regression and, in fact, the odds ratios for
> serious mental illness and use-dependence are greater than the odds ratio for
> SMI and no use - use. My question, after that longish preamble, is can you
> compare the odds ratios against each other to see if they are significantly
> different? Or equivalently and perhaps more understandably, can you test the
> ordered logistic regression assumption that the effect size for a predictor
> variable is the same across the ordered levels of the dependent variable?
>
> Thanks for any help!
>
> James
> [email protected]
>
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