Review of the Methods for Handling Missing Data in Longitudinal Data Analysis


Even in well-controlled situations, missing data always occur in longitudinal data analysis. Missing data may degrade the performance of confidence intervals, reduce statistical power and bias parameter estimate. In this paper, we review and discuss general approaches for handling miss data in longitudinal studies. We first illustrate the mechanism of… (More)


  • Presentations referencing similar topics