A hidden Markov model for informative dropout in longitudinal response data with crisis states (2011)

Author(s): Spagnoli A, Henderson R, Boys RJ, Houwing-Duistermaat JJ

    Abstract: We adopt a hidden state approach for the analysis of longitudinal data subject to dropout. Motivated by two applied studies, we assume that subjects can move between three states: stable, crisis, dropout. Dropout is observed but the other two states are not. During a possibly transient crisis state both the longitudinal response distribution and the probability of dropout can differ from those for the stable state. We adopt a linear mixed effects model with subject-specific trajectories during stable periods and additional random jumps during crises. We place the model in the context of Rubin’s taxonomy and develop the associated likelihood. The methods are illustrated using the two motivating examples.

      • Date: 17-02-2011
      • Journal: Statistics and Probability Letters
      • Volume: 81
      • Issue: 7
      • Pages: 730-738
      • Publisher: Elsevier BV
      • Publication type: Article
      • Bibliographic status: Published

      Keywords: Change points; Monotonic missing data; Mixed models; Random effects; State space


      Professor Richard Boys
      Professor of Applied Statistics

      Professor Robin Henderson
      Professor of Statistics