Three Underused Statistical Methods in Social Epidemiology: Multiple Informant Models, Fractional Regression, and Restricted Mean Survival Time

Abstract We recommend three well-established yet underused statistical methods in social epidemiology: Multiple Informant Models (MIMs), Fractional Regression Model (FRM), and Restricted Mean Survival Time (RMST). MIMs improve how we identify critical windows of exposure over time. FRM addresses the inadequacies of ordinary least squares and logistic regression when dealing with fractional outcomes that are naturally proportions or rates, thereby accommodating data at the boundaries of the unit interval without requiring transformations. RMST offers a robust alternative to the hazard ratio in the presence of non-proportional hazards, providing an interpretable summary of treatment effects over time that is not dependent on the proportional hazards assumption. We illustrate the utility of each method using simulated case examples. These methodologies enrich the analytical toolbox of social epidemiologists, offering refined approaches to unraveling the complexities of social determinants of health inequities.