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dc.contributor.authorJiang, Shu
dc.contributor.authorCook, Richard J.
dc.contributor.authorZeng, Leilei 15:03:53 (GMT) 15:03:53 (GMT)
dc.descriptionThis is the peer reviewed version of the following article: Shu Jiang, Richard J. Cook and Leilei Zeng, Mitigating bias from intermittent measurement of time-dependent covariates in failure time analysis, Statistics in Medicine (2020), 39 (13): 1833–1845 which has been published in final form at 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.abstractCox regression models are routinely fitted to examine the association between time-dependent markers and a failure time when analyzing data from clinical registries. Typically, the marker values are measured periodically at clinic visits with the recorded value carried forward until the next assessment. We examine the asymptotic behavior of estimators from Cox regression models under this observation and data handling scheme when the true relationship is based on a Cox model using the current value of the marker. Specifically, we explore the impact of the marker process dynamics, the clinic visit intensity, and the marginal failure rate on the limiting value of the estimator of the marker effect from the Cox model. We also illustrate how a joint multistate model that accommodates intermittent observation of the time-varyingmarker can be formulated. Simulation studies demonstrate that the finite sample performance of the naive estimator aligns with the asymptotic results and shows good performance of the estimators from the joint model. We apply both methods to data from a study of bone markers and their effect on the development of skeletal complications in metastatic cancer.en
dc.description.sponsorshipThis research was supported by Discovery Grants from the Natural Sciences and Engineering Research Council of Canada to R.J.C. (RGPIN 155849 and RGPIN 04207) and L.Z. (RGPIN 115928) and from the Canadian Institutes for Health Research to R.J.C. (FRN 13887). R.J.C. is a Faculty of Mathematics Research Chair, University of Waterloo.en
dc.relation.ispartofseriesStatistics in Medicine;39(13)
dc.subjectCox modelen
dc.subjectintermittent observationen
dc.subjectmodel misspecificationen
dc.subjecttime-dependent covariatesen
dc.titleMitigating bias from intermittent measurement of time-dependent covariates in failure time analysisen
dcterms.bibliographicCitationJiang, S, Cook, RJ, Zeng, L. Mitigating bias from intermittent measurement of time‐dependent covariates in failure time analysis. Statistics in Medicine. 2020; 39: 1833– 1845.
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen

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