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We present a three-step likelihood inference approach for the analysis of multidimensional longitudinal data when a large number of response variables are collected at each time occasion. We show the results obtained using this method to identify patients with different levels of Myasthenia Gravis severity and assess symptom progression over time.

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Dynamic Classification Through Three-Step Estimation: Evidence from a Multinational Longitudinal Study of Myasthenia Gravis Patients

  • 会议论文

  • 发表日期：

    2025年

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  • Luca Brusa,
  • Fulvia Pennoni,
  • Francesco Bartolucci,
  • Lorenzo Maggi

摘要

We present a three-step likelihood inference approach for the analysis of multidimensional longitudinal data when a large number of response variables are collected at each time occasion. We show the results obtained using this method to identify patients with different levels of Myasthenia Gravis severity and assess symptom progression over time.