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Pattern Recognition Of Longitudinal Trial Data With Nonignorable Missingness: An Empirical Case Study

Author

Listed:
  • HUA FANG

    (Office of Research, University of Nebraska-Lincoln, Lincoln, NE 68588, USA)

  • KIMBERLY ANDREWS ESPY

    (Office of Research, University of Nebraska-Lincoln, Lincoln, NE 68588, USA)

  • MARIA L. RIZZO

    (Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, Ohio 43403, USA)

  • CHRISTIAN STOPP

    (Office of Research, University of Nebraska-Lincoln, Lincoln, NE 68588, USA)

  • SANDRA A. WIEBE

    (Office of Research, University of Nebraska-Lincoln, Lincoln, NE 68588, USA)

  • WALTER W. STROUP

    (Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE 68588, USA)

Abstract

Methods for identifying meaningful growth patterns of longitudinal trial data with both nonignorable intermittent and drop-out missingness are rare. In this study, a combined approach with statistical and data mining techniques is utilized to address the nonignorable missing data issue in growth pattern recognition. First, a parallel mixture model is proposed to model the nonignorable missing information from a real-world patient-oriented study and concurrently to estimate the growth trajectories of participants. Then, based on individual growth parameter estimates and their auxiliary feature attributes, a fuzzy clustering method is incorporated to identify the growth patterns. This case study demonstrates that the combined multi-step approach can achieve both statistical generality and computational efficiency for growth pattern recognition in longitudinal studies with nonignorable missing data.

Suggested Citation

  • Hua Fang & Kimberly Andrews Espy & Maria L. Rizzo & Christian Stopp & Sandra A. Wiebe & Walter W. Stroup, 2009. "Pattern Recognition Of Longitudinal Trial Data With Nonignorable Missingness: An Empirical Case Study," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 491-513.
    • Handle: RePEc:wsi:ijitdm:v:08:y:2009:i:03:n:s0219622009003508
    DOI: 10.1142/S0219622009003508
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