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Re: st: weighted logistic regression in stata

From   Steve Samuels <>
Subject   Re: st: weighted logistic regression in stata
Date   Wed, 20 Jun 2012 09:12:34 -0400

You are describing what used to be called the "errors in variables" problem; now
it is known as the "measurement error" problem.

The kind of weighting you describe does not solve this problem, as far as I
know. (I'd be happy to learn otherwise.) It is ordinarily used to accommodate
outcomes, not covariates, that are measured with unequal precision. In this
application, the weights are known as "analytic" weights (in Stata, "aweights"; see the -help- for "weights")

For Stata solutions to the problem of measurement error in covariates. See .


On Jun 19, 2012, at 7:32 PM, Katherine Nishimura wrote:

I have an epidemiologic dataset and want to do a weighted logistic
regression.  I have a continuous exposure variable that I want to see
if it is associated with a binary outcome.  The accuracy of the
exposure variable is highly variable and I want to do a logistic
regression with assigns greater weight to exposure values that are
highly accurate, and lower weight to values that have lower accuracy.
Can stata do this type of analysis?  What command should I use?
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