
From  Richard Williams <Richard.A.Williams.5@ND.edu> 
To  statalist@hsphsun2.harvard.edu 
Subject  Re: st: Wald ChiSquare in Logistic with Cluster Option 
Date  Sat, 11 Mar 2006 19:06:13 0500 
At 05:25 PM 3/11/2006, you wrote:
Thanks to Clive for the kind words. Alas, much as I'd like to claim credit for collin (along with xtabond2 and several other programs!) the actual author is Phil Ender and you need to get it from UCLA, not SSC. Just use findit collin to get a copy.The good news is that, assuming your logistic model specifications are correct, then your Wald value is OK. It may be that some of your variables are highly collinear with each other, and it's that that's pushing it up a few notches: you can check this with Richard Williams' highly useful collin postestimation command, downloadable from SSC.
Not quite. The problem comes in comparing coefficients across models, e.g. you have x1, x2 and x3 in a model, you then add x4, x5 and x6, and you observe that the coefficients for x1, x2 and x3 are quite a bit different in the two models. This is a fairly common thing to do with OLS regression models, but, for reasons explained in the handout, can be highly deceptive when doing things like logistic regression. But, that doesn't mean that you can't run a series of models, and see whether adding or deleting variables significantly affects the fit of the model.The bad news is that comparing two logistic regression models, even if they both have some independent variables in common, is _wrong_. For the full reasoning, you can check out a neat .pdf file from that man again Williams at http://www.nd.edu/%7Erwilliam/xsoc694/x04.pdf
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