Multiple imputation in a longitudinal cohort study: A case study of sensitivity to imputation methods

Abstract

Multiple imputation has entered mainstream practice for the analysis of incomplete data. We have used it extensively in a large Australian longitudinal cohort study, the Victorian Adolescent Health Cohort Study (1992-2008). Although we have endeavored to follow best practices, there is little published advice on this, and we have not previously examined the extent to which variations in our approach might lead to different results. Here, we examined sensitivity of analytical results to imputation decisions, investigating choice of imputation method, inclusion of auxiliary variables, omission of cases with excessive missing data, and approaches for imputing highly skewed continuous distributi..