BackgroundMultiple imputation has become very popular as a general-purpose method for handling missing data. The validity of multiple-imputation-based analyses relies on the use of an appropriate model to impute the missing values. Despite the widespread use of multiple imputation, there are few guidelines available for checking imputation models. AnalysisIn this paper, we provide an overview of currently available methods for checking imputation models. These include graphical checks and numerical summaries, as well as simulation-based methods such as posterior predictive checking. These model checking techniques are illustrated using an analysis affected by missing data from the Longitudinal Study of Australian Children.ConclusionsAs multiple imputation becomes further established as a standard approach for handling missing data, it will become increasingly important that researchers employ appropriate model checking approaches to ensure that reliable results are obtained when using this method. Electronic supplementary materialThe online version of this article (doi:10.1186/s12982-017-0062-6) contains supplementary material, which is available to authorized users.

IMPORTANCE Although multiple cross-sectional and longitudinal studies have established that sleep problems and behavioral difficulties are associated in children, the directionality of this association and whether sleep problems are differentially associated with different types of childhood behavioral difficulties are unclear. Understanding these associations will inform the focus and timing of interventions. OBJECTIVE To determine whether longitudinal and reciprocal associations exist between child sleep problems and externalizing, internalizing, or both behavioral difficulties.