On a closed-form doubly robust estimator of the adjusted odds ratio for a binary exposure.

ABSTRACT: Epidemiologic studies often aim to estimate the odds ratio for the association between a binary exposure and a binary disease outcome. Because confounding bias is of serious concern in observational studies, investigators typically estimate the adjusted odds ratio in a multivariate logistic regression which conditions on a large number of potential confounders. It is well known that modeling error in specification of the confounders can lead to substantial bias in the adjusted odds ratio for exposure. As a remedy, Tchetgen Tchetgen et al. (Biometrika. 2010;97(1):171-180) recently developed so-called doubly robust estimators of an adjusted odds ratio by carefully combining standard logistic regression with reverse regression analysis, in which exposure is the dependent variable and both the

SUBMITTER: Tchetgen Tchetgen EJ 

PROVIDER: S-EPMC3664333 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature