Methods for estimating adjusted risk ratios

被引:253
作者
Cummings, Peter [1 ,2 ]
机构
[1] Univ Washington, Sch Publ Hlth, Dept Epidemiol, Seattle, WA 98195 USA
[2] Univ Washington, Harborview Injury Prevent & Res Ctr, Seattle, WA 98195 USA
关键词
st0162; risk ratio; odds ratio; MAXIMUM-LIKELIHOOD METHODS; RARE DISEASE ASSUMPTION; RELATIVE RISK; CONFIDENCE-INTERVALS; CLINICAL-TRIALS; COHORT METHODS; ODDS-RATIO; REGRESSION; COVARIANCE; OUTCOMES;
D O I
10.1177/1536867X0900900201
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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, including 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 logistic, probit, complementary log-log, and log-log regression; and 7) a substitution method. Advantages and drawbacks are noted for some methods.
引用
收藏
页码:175 / 196
页数:22
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