On Modeling and Estimation for the Relative Risk and Risk Difference
Methodology
2016-11-21 v4 Applications
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.
Keywords
Cite
@article{arxiv.1510.02430,
title = {On Modeling and Estimation for the Relative Risk and Risk Difference},
author = {Thomas S. Richardson and James M. Robins and Linbo Wang},
journal= {arXiv preprint arXiv:1510.02430},
year = {2016}
}
Comments
To appear in Journal of the American Statistical Association: Theory and Methods