RESEARCH ARTICLE Open Access Multiple

imputation for estimation of an occurrence rate in cohorts with attrition and discrete follow-up time points: a simulation study Noémie Soullier1,2,3, Elise de La Rochebrochard1,2,3, Jean Bouyer1,2,3* Background: In longitudinal cohort studies, subjects may be lost to follow-up at any time during the study. This leads to attrition and thus to a risk of inaccurate and biased estimations. The purpose of this paper is to show how multiple imputation can take advantage of all the information collected during follow-up in order to estimate the cumulative probability P(E) of an event E, when the first occurrence of this event is observed at t successive time points of a longitudinal study with attrition. Methods: We compared the performance of multiple imputation with that of Kaplan-Meier estimation in several simulated attrition scenarios. Results: In missing-completely-at-random scenarios, the multiple imputation and Kaplan-Meier methods performed well in terms of bias (less than 1%) and coverage rate (range = [94.4%; 95.8%]). In missing-at-random scenarios, the Kaplan-Meier method was associated with a bias ranging from-5.1 % to 7.0 % and with a very poor coverage rat