Computing adjusted risk ratios and risk differences in Stata

Edward Norton, Morgen M. Miller () and Lawrence C. Kleinman ()
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Morgen M. Miller: University of Michigan - Ann Arbor
Lawrence C. Kleinman: Icahn School of Medicine at Mount Sinai

Stata Journal, 2013, vol. 13, issue 3, 492-509

Abstract: In this article, we explain how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata’s margins command, we create a new postestimation command, adjrr, that calculates adjusted risk ratios and adjusted risk differences after running a logit or probit model with a binary, a multinomial, or an ordered outcome. adjrr reports the point estimates, delta-method standard errors, and 95% confidence intervals and can compute these for specific values of the variable of interest. It automatically adjusts for complex survey design as in the fit model. Data from the Medical Expenditure Panel Survey and the National Health and Nutrition Examination Survey are used to illustrate multiple applications of the command. Copyright 2013 by StataCorp LP.

Keywords: adjrr; risk ratio; adjusted risk ratio; risk difference; adjusted risk difference; odds ratio; logistic; logit; probit; multinomial; ordered (search for similar items in EconPapers)
Date: 2013
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