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Nonparametric inference under a monotone hazard ratio order

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dc.contributor.authorWu, Yujian
dc.contributor.authorWestling, Ted
dc.date2024-04-02T15:34:59.000
dc.date.accessioned2024-04-26T18:40:03Z
dc.date.available2024-03-25T00:00:00Z
dc.date.issued2023-01-01
dc.description.abstractThe ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to estimate the hazard ratio under the assumption that it is constant in time, which is known as the proportional hazards assumption. However, this assumption is often violated in practice, and when it is violated, the parameter estimated by Cox regression is difficult to interpret. The hazard ratio can be estimated in a nonparametric manner using smoothing, but smoothing-based estimators are sensitive to the selection of tuning parameters, and it is often difficult to perform valid inference with such estimators. In some cases, it is known that the hazard ratio function is monotone. In this article, we demonstrate that monotonicity of the hazard ratio function defines an invariant stochastic order, and we study the properties of this order. Furthermore, we introduce an estimator of the hazard ratio function under a monotonicity constraint. We demonstrate that our estimator converges in distribution to a mean-zero limit, and we use this result to construct asymptotically valid confidence intervals. Finally, we conduct numerical studies to assess the finite-sample behavior of our estimator, and we use our methods to estimate the hazard ratio of progression-free survival in pulmonary adenocarcinoma patients treated with gefitinib or carboplatin-paclitaxel.
dc.identifier.doihttps://doi.org/10.1214/23-EJS2173
dc.identifier.urihttps://hdl.handle.net/20.500.14394/34410
dc.relation.ispartofElectronic Journal of Statistics
dc.relation.urlhttps://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2348&context=math_faculty_pubs&unstamped=1
dc.rightsUMass Amherst Open Access Policy
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.source.issue17
dc.source.statuspublished
dc.subjecthazard ratio
dc.subjectnonparametric inference
dc.subjectShape constrained estimation
dc.subjectStochastic orders
dc.subjectSurvival analysis
dc.subjecttime-varying treatment
dc.titleNonparametric inference under a monotone hazard ratio order
dc.typearticle
dc.typearticle
digcom.contributor.authorWu, Yujian
digcom.contributor.authorWestling, Ted
digcom.date.embargo2024-03-25T00:00:00-07:00
digcom.identifiermath_faculty_pubs/1349
digcom.identifier.contextkey36821471
digcom.identifier.submissionpathmath_faculty_pubs/1349
dspace.entity.typePublication
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