On Modeling and Estimation for the Relative Risk and Risk Difference. Issue 519 (3rd July 2017)

• Record Type: Journal Article
• Authors: Richardson, Thomas S.; Robins, James M.; Wang, Linbo
• Is Part Of: Journal of the American Statistical Association. Volume 112:Issue 519(2017)
• Page Start: 1121
• Page End: 1130
• Publication Date: 2017-07-03
• Subjects: Bivariate mapping -- Estimating equation -- Semiparametric model -- Variation independence; Statistics -- Periodicals; Statistics -- Periodicals; Statistiques -- Périodiques; États-Unis -- Statistiques -- Périodiques; 519.5
• DOI: 10.1080/01621459.2016.1192546
• Languages: English
• ISSNs: 0162-1459

Abstract

ABSTRACT: A common problem in formulating models for the relative risk and risk difference is the variation dependence between these parameters and the baseline risk, which is a nuisance model. We address this problem by proposing the conditional log odds-product as a preferred nuisance model. This novel nuisance model facilitates maximum-likelihood estimation, but also permits doubly-robust estimation for the parameters of interest. Our approach is illustrated via simulations and a data analysis. An R package implementing the proposed methods is available on CRAN. Supplementary materials for this article are available online.