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State duration models in clinical and observational studies
Author(s) -
Lawless J. F.,
Fong D. Y. T.
Publication year - 1999
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19990915/30)18:17/18<2365::aid-sim262>3.0.co;2-q
Subject(s) - observational study , econometrics , inference , duration (music) , set (abstract data type) , random effects model , causal inference , markov model , computer science , statistics , markov chain , mathematics , artificial intelligence , medicine , meta analysis , art , literature , programming language
Many studies in medicine involve conditions whereby subjects make transitions among a set of defined states over time. In such situations the durations of sojourns in specific states is frequently of interest. This article considers the modelling and analysis of sojourn times, beginning with semi‐Markov models in which the durations of different sojourns are independent, and then considering extended models incorporating chronological time effects and random effects. Methodologic challenges for inference are discussed, and examples involving a relapse‐remitting process and recurrent events are considered. Copyright © 1999 John Wiley & Sons, Ltd.