Bigotry in Last Observation Carried Forward (LOCF) Analysis

Abstract

Last observation carried forward is a common statistical approach to the analysis of longitudinal repeated measures data where some follow-up observations may be missing. To accurately estimate the magnitude of treatment efficacy, caution should be observed regarding the LOCF analytical bias. To conciliate with this challenge, several imputation methods have been developed in the literature to handle missing values where the most commonly used are complete case method, mean imputation method, last observation carried forward (LOCF) method and multiple imputation (MI) method. Subsequently after rigorous review, this paper concludes that LOCF method has more bias than the other three methods in most situations.