Missing Data in Longitudinal Surveys: A Comparison of Performance of Modern Techniques
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Nov 1, 2017
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Paola Zaninotto
University College London, London, UK
Amanda Sacker
University College London, London, UK
Abstract
Using a simulation study, the performance of complete case analysis, full information maximum likelihood, multivariate normal imputation, multiple imputation by chained equations and two-fold fully conditional specification to handle missing data were compared in longitudinal surveys with continuous and binary outcomes, missing covariates, and an interaction term.
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