  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.
