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

نویسندگان

  • Michikazu Nakai
  • Weiming Ke
چکیده

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 missing data. Then we focus on the methods for handling missing values in longitudinal data analysis. In the end, we summarize and discuss the characteristics of each method. Mathematical Subject Classification: 62J10, 62J12, 62-07

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تاریخ انتشار 2010