On the application of linear relative risk regression models.

Motivations for considering linear relative risk models are described. These include covariate data reduction and the testing of additivity of covariate effects on the relative risk. A simulation study was conducted in order to study properties of asymptotic distributional approximations and iterative convergence properties. Parameter transformations and likelihood ratio approximations are considered for confidence interval calculation.