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Many longitudinal studies, especially in clinical trials, suffer from missing data issues. Most estimation procedures assume that the missing values are ignorable or missing at random (MAR). However, this assumption

Many longitudinal studies, especially in clinical trials, suffer from missing data issues. Most estimation procedures assume that the missing values are ignorable or missing at random (MAR). However, this assumption leads to unrealistic simplification and is implausible for many cases. For example, an investigator is examining the effect of treatment on depression. Subjects are scheduled with doctors on a regular basis and asked questions about recent emotional situations.

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    Date Created
    • 2013
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  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2013
      Note type
      thesis
    • Includes bibliographical references (p. 123-127)
      Note type
      bibliography
    • Field of study: Statistics

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    by Jun Zhang

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