How to handle missing data: A comparison of different approaches
Many researchers face the problem of missing data in longitudinal research. Especially, high risk samples are characterized by missing data which can complicate analyses and the interpretation of results.
Reducing bias due to systematic attrition in longitudinal studies: The benefits of multiple imputation
Most longitudinal studies are plagued by drop-out related to variables at earlier assessments (systematic attrition). Although systematic attrition is often analysed in longitudinal studies, surprisingly few researchers attempt to reduce biases due to systematic attrition, even though this is possible and nowadays technically easy.