Score tests based on a finite mixture model of Markov processes under intermittent observation
| dc.contributor.author | Jiang, Shu | |
| dc.contributor.author | Cook, Richard J. | |
| dc.date.accessioned | 2021-01-13T15:03:30Z | |
| dc.date.available | 2021-01-13T15:03:30Z | |
| dc.date.issued | 2019-07-20 | |
| dc.description | This is the peer reviewed version of the following article: Shu Jiang and Richard J. Cook, Score tests based on a finite mixture model of Markov processes under intermittent observation, Statistics in Medicine (2019), 38(16): 3013–3025 which has been published in final form at https://doi.org/10.1002/sim.8155. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | en |
| dc.description.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. | en |
| dc.description.sponsorship | This research was supported through grants from the Natural Sciences and Engineering Research Council of Canada (RGPIN 155849 and RGPIN 04027) and the Canadian Institutes for Health Research (FRN 13887) awarded to Richard Cook. Richard Cook is a Tier I Canada Research Chair in Statistical Methods for Health Research. | en |
| dc.identifier.uri | https://doi.org/10.1002/sim.8155 | |
| dc.identifier.uri | http://hdl.handle.net/10012/16638 | |
| dc.language.iso | en | en |
| dc.publisher | Wiley | en |
| dc.relation.ispartofseries | Statistics in Medicine;38(16) | |
| dc.subject | finite mixture model | en |
| dc.subject | intermittent observation | en |
| dc.subject | Markov process | en |
| dc.subject | multistate model | en |
| dc.subject | score test | en |
| dc.title | Score tests based on a finite mixture model of Markov processes under intermittent observation | en |
| dc.type | Article | en |
| dcterms.bibliographicCitation | Jiang, S, Cook, RJ. Score tests based on a finite mixture model of Markov processes under intermittent observation. Statistics in Medicine. 2019; 38: 3013– 3025. https://doi.org/10.1002/sim.8155 | en |
| uws.contributor.affiliation1 | Faculty of Mathematics | en |
| uws.contributor.affiliation2 | Statistics and Actuarial Science | en |
| uws.peerReviewStatus | Reviewed | en |
| uws.scholarLevel | Faculty | en |
| uws.typeOfResource | Text | en |