Missing data methods in longitudinal studies: a review

@article{Ibrahim2009MissingDM,
  title={Missing data methods in longitudinal studies: a review},
  author={J. Ibrahim and G. Molenberghs},
  journal={TEST},
  year={2009},
  volume={18},
  pages={1-43}
}
  • J. Ibrahim, G. Molenberghs
  • Published 2009
  • Mathematics
  • TEST
  • Incomplete data are quite common in biomedical and other types of research, especially in longitudinal studies. During the last three decades, a vast amount of work has been done in the area. This has led, on the one hand, to a rich taxonomy of missing-data concepts, issues, and methods and, on the other hand, to a variety of data-analytic tools. Elements of taxonomy include: missing data patterns, mechanisms, and modeling frameworks; inferential paradigms; and sensitivity analysis frameworks… CONTINUE READING
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