On Modeling and Estimation for the Relative Risk and Risk Difference

By Thomas S. Richardson, James M. Robins, Linbo Wang. 2015

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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.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b66a477a398fc2c4e3cb154be38aeb920c3d57bb