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# Re: st: How to obtain intercepts using svyologit

 From Richard Williams To statalist@hsphsun2.harvard.edu Subject Re: st: How to obtain intercepts using svyologit Date Mon, 21 Feb 2005 19:39:07 -0500

```At 03:05 PM 2/21/2005 +0800, YP Choi wrote:
```
```Dear all,

I am using the survey commands in stata to analyze stratified data. I am
running some ordinal logistic regressing models and want to know how I can
obtain the odds ratio of the intercepts?
Many thanks for your help.
```
Somebody can correct me if I am wrong, but I don't believe the term "odds ratio" is appropriate when referring to the intercept (which is why Stata doesn't report it in the column labeled odds ratio; although other programs like SPSS will have a column labeled EXP(B) which includes the intercept). The idea of the odds ratio is that you are contrasting the odds of 2 otherwise identical cases where one case scores 1 unit higher on the X variable in question. For a constant, this doesn't make any sense, since all cases have a score of one on the constant.

Nonetheless, in some contexts, you might be interested in the exponentiated intercept, e.g. in a logistic regression, an intercept of zero would tell you that somebody who scored 0 on all the Xs would have exp(0) = 1 odds of success, which corresponds to a 50% chance of success. If the intercept was 1, the probability of success for somebody scoring 0 on all the Xs would be 73.1%. If there are no Xs in the model, e.g. you just do -logit y- , then the exponentiated intercept gives you the overall odds of success.

In ordinal logistic regression, however, Stata reports cutpoints, not intercepts. Again, maybe somebody can enlighten me here, but I am not sure what an exponentiated cutpoint would mean, at least when there is more than 1 cutpoint. (If there is only 1 cutpoint, it has the same value but opposite sign of what you get when you run a logistic regression.)

But, if you really want exponentiated intercepts or cutpoints, there is always your calculator, or the -display- command in Stata.

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Richard Williams, Notre Dame Dept of Sociology
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