Due to the intraindividual dependence, specific analytic strategies are needed to assess risk factors for recurrent events. Although well established in the biostatistics literature, applications of these techniques are almost nonexistent in the field of epidemiology. The authors applied four different regression approaches for recurrent events (logistic, Poisson, and two different Cox proportional hazards regressions) to derive rate ratios of hospitalizations for various prognostic factors in a cohort of 2424 frail elderly. Over a median follow-up of 670 days, 3299 hospitalizations were observed in 1564 persons. Estimated rate ratios were similar in all four approaches and virtually identical in three. With all methods, confidence intervals of the rate ratios were considerably wider than with naive Poisson regression neglecting intraindividual dependence of events. Appropriate analysis of recurrent events is feasible with minor modifications of multivariable models familiar to epidemiologists and should no longer be neglected in epidemiologic research. In our setting, Poisson regression was the most convenient approach.