A hidden Markov model for informative dropout in longitudinal response data with crisis states. (English) Zbl 1217.62193
Summary: 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 D. B. Rubin’s [Biometrika 63, 581–592 (1976; Zbl 0344.62034)] taxonomy and develop the associated likelihood. The methods are illustrated using the two motivating examples.
MSC:
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
| 65J05 | General theory of numerical analysis in abstract spaces |
| 62M99 | Inference from stochastic processes |
| 65C60 | Computational problems in statistics (MSC2010) |
Citations:
Zbl 0344.62034References:
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