# Re: st: Binomial regression

 From David Bell To statalist@hsphsun2.harvard.edu Subject Re: st: Binomial regression Date Fri, 3 Aug 2007 17:35:45 -0400

If you use an identity link, you are assuming that, given a difference in the independent variables that produces a change from . 50 to .60 in the probability represented by your dependent variable, the same difference will also produce a change from .90 to 1.00 or from .95 to 1.05. I can't imagine many real world processes that would fit that model.
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David C. Bell
Professor of Sociology
Indiana University Purdue University Indianapolis (IUPUI)
(317) 278-1336
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On Aug 2, 2007, at 4:28 PM, Constantine Daskalakis wrote:

No argument about logistic regression. But that gives you odds ratios. What if you want risk differences instead?

There are several good reasons why we might want binomial regression (RD) instead of logistic regression (OR):

(i) Easier conceptual interpretation (RD vs. OR).

(ii) Causal effects interpretation (the RD can have it, but not the OR).

(iii) Effects of independent variables may be more additive on the original risk scale rather than on the log-odds scale (thus, logistic regression would need lots of interaction terms to get a good fit).

(iv) Because the reviewer/editor/boss fancies it.

By the way, there is no inherently "more appropriate" link function for a particular type of outcome. It's just that some are technically easier than others.

Best,
CD

On 8/2/2007 3:07 PM, Maarten buis wrote:

This may be a silly question, but why are you using the identity link?
It is not very appropriate for a binary dependent variable since it
will eventually lead to prediction outside the allowable range, and
apperently there are also problems with getting the model to converge.
Logit and probit links will converge in no time in Stata (probably also
in SAS), and are more appropriate for binary dependent variables.
Maarten

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