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.