Strategies for multiple imputation in longitudinal studies

Abstract

Multiple imputation is increasingly recommended in epidemiology to adjust for the bias and loss of information that may occur in analyses restricted to study participants with complete data ("complete-case analyses"). However, little guidance is available on applying the method, including which variables to include in the imputation model and the number of imputations needed. Here, the authors used multiple imputation to analyze the prevalence of wheeze among 81-month-old children in the Avon Longitudinal Study of Parents and Children (Avon, United Kingdom; 1991-1999) and the association of wheeze with gender, maternal asthma, and maternal smoking. The authors examined how inclusion of diffe..