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Methods for estimating adjusted risk ratios

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  • Peter Cummings

    (University of Washington)

Abstract

The risk ratio can be a useful statistic for summarizing the results of cross-sectional, cohort, and randomized trial studies. I discuss several methods for estimating adjusted risk ratios and show how they can be executed in Stata, in- cluding 1) Mantel – Haenszel and inverse-variance stratified methods; 2) generalized linear regression with a log link and binomial distribution; 3) generalized linear regression with a log link, normal distribution, and robust variance estimator; 4) Poisson regression with a robust variance estimator; 5) Cox proportional hazards regression with a robust variance estimator; 6) standardized risk ratios from logis- tic, probit, complementary log-log, and log-log regression; and 7) a substitution method. Advantages and drawbacks are noted for some methods. Copyright 2009 by StataCorp LP.

Suggested Citation

  • Peter Cummings, 2009. "Methods for estimating adjusted risk ratios," Stata Journal, StataCorp LLC, vol. 9(2), pages 175-196, June.
    • Handle: RePEc:tsj:stataj:v:9:y:2009:i:2:p:175-196
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    3. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    4. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
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