Practice of epidemiology multiple imputation in a longitudinal cohort study: acase study of sensitivity to imputation methods... Multiple imputation by chained equations gave more plausible results than multivariate normal imputation for prevalence estimates but appeared to be more susceptible to numerical instability related to a highly skewed variable....
Missing data in longitudinal surveys: a comparison of performance of modern techniquesUsing 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...
Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study... We compared the performance of fully conditional specification with multinomial and ordinal logistic imputation, and predictive mean matching, two-fold fully conditional specification, indicator based imputation under multivariate normal imputation with projected distance-based rounding, and continuous imputation under multivariate normal imputation with calibration, where each of these multiple imputation...
Multiple imputation for handling missing outcome data when estimating the relative risk... Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome....
