On Modeling and Estimation for the Relative Risk and Risk Difference

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 nuis...

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Bibliographic Details
Published in:Journal of the American Statistical Association 2017-07, Vol.112 (519), p.1121-1130
Main Authors: Richardson, Thomas S., Robins, James M., Wang, Linbo
Format: Article
Language:English
Subjects:
Bivariate mapping
Estimating equation
Semiparametric model
Theory and Methods
Variation independence
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Summary: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.
ISSN:0162-1459
1537-274X
DOI:10.1080/01621459.2016.1192546