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

被引：7

作者：

Spagnoli, Alessandra ^{[1
]}

Henderson, Robin ^{[2
]}

Boys, Richard J. ^{[2
]}

Houwing-Duistermaat, Jeanine J. ^{[3
]}

机构：

[1] Univ Roma La Sapienza, Dipartimento Sci Stat, I-00185 Rome, Italy

[2] Newcastle Univ, Sch Math & Stat, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[3] LUMC, Dept Med Stat & Bioinformat, Leiden, Netherlands

来源：

STATISTICS & PROBABILITY LETTERS | 2011年 / 81卷 / 07期

关键词：

Change points; Monotonic missing data; Mixed models; Random effects; State space; NUISANCE PARAMETER; DECLINE;

D O I：

10.1016/j.spl.2011.02.005

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：730 / 738

页数：9

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