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Score tests based on a finite mixture model of Markov processes under intermittent observation.

Authors
  • Jiang, Shu1
  • Cook, Richard J1
  • 1 Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada. , (Canada)
Type
Published Article
Journal
Statistics in Medicine
Publisher
Wiley (John Wiley & Sons)
Publication Date
Jul 20, 2019
Volume
38
Issue
16
Pages
3013–3025
Identifiers
DOI: 10.1002/sim.8155
PMID: 30972787
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

A mixture model is described, which accommodates different Markov processes governing disease progression in a finite set of latent classes. We give special attention to the setting in which individuals are examined intermittently and transition times are consequently interval censored. A score test is developed to identify genetic markers associated with class membership. Simulation studies are conducted to validate the algorithm, assess the finite sample properties of the estimators, and assess the frequency properties of the score tests. A permutation test is recommended for settings when there is concern that the asymptotic approximation to the score test is poor. An application involving progression in joint damage in psoriatic arthritis (PsA) provides illustration and identifies human leukocyte antigen markers associated with unilateral and bilateral sacroiliac damage in individuals with PsA. © 2019 John Wiley & Sons, Ltd.

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