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.
DOI
10.22237/jmasm/1509495600
Recommended Citation
Zaninotto, P., & Sacker, A. (2017). Missing Data in Longitudinal Surveys: A Comparison of Performance of Modern Techniques. Journal of Modern Applied Statistical Methods, 16(2), 378-402. doi: 10.22237/jmasm/1509495600
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
