A comparison is made between two different approaches to the linear logistic regression analysis of retrospective study data: the prospective model wherein the dependent variable is a dichotomous indicator of case/control status; and the retrospective model wherein the dependent variable is a binary or polychotomous classification of exposure. The two models yield increasingly similar estimates of the relative risk with increasing degrees of covariate adjustment. When the covariate effects are saturated with parameters, the relative risk estimates are identical. The prospective model is generally to be preferred for studies involving multiple quantitative risk factors.