Risk Ratio Estimation in Longitudinal Studies

Longitudinal studies are very common in medical, behavioral, and interventional sciences. One measure of effect of interest in longitudinal studies is risk ratio, naturally estimated by log-binomial regression which suffers from convergence problem. Odds ratio does not well approximate risk ratio when the outcome is common, so alternative methods have been introduced in cohort studies with one follow-up visit. In this paper, we illustrate 2 simple methods, COPY method and modified log-Poisson regression for risk ratio estimation in longitudinal data setting. Our unpublished simulation study on risk ratio estimation in longitudinal data setting suggests that COPY method performs well in terms of closeness of the risk ratio estimate and true risk ratio (mean square error) and so we suggest this method for risk ratio estimation in longitudinal Longitudinal studies are very common in medical, behavioral, and interventional sciences. One measure of effect of interest in longitudinal studies is risk ratio, naturally estimated by log-binomial regression which suffers from convergence problems. Odds ratio (OR) does not approximate risk ratio (RR) well when the outcome is common, so alternative methods have been introduced in cohort studies with one follow-up visit. In this paper, we illustrate two simple methods: the COPY method and the modified log-Poisson regression for RR estimation in longitudinal data setting. Our unpublished simulation study on RR estimation in longitudinal data setting suggests that the COPY method performs well in terms of closeness of the RR estimate and true RR (mean square error) and so we suggest this method for RR estimation in longitudinal data setting.data setting.