Computing Adjusted Risk Ratios and Risk Differences in Stata
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.
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Article first published online: September 1, 2013
Issue published: September 2013
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Published online: September 1, 2013
Issue published: September 2013
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This article was published in The Stata Journal: Promoting communications on statistics and Stata.
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