Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93875
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Hu, X | en_US |
dc.creator | Huang, J | en_US |
dc.creator | Liu, L | en_US |
dc.creator | Sun, D | en_US |
dc.creator | Zhao, X | en_US |
dc.date.accessioned | 2022-08-03T01:24:02Z | - |
dc.date.available | 2022-08-03T01:24:02Z | - |
dc.identifier.issn | 0277-6715 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93875 | - |
dc.language.iso | en | en_US |
dc.publisher | John Wiley & Sons | en_US |
dc.rights | © 2020 John Wiley & Sons, Ltd. | en_US |
dc.rights | This is the peer reviewed version of the following article: Hu, X., Huang, J., Liu, L., Sun, D., & Zhao, X. (2021). Subgroup analysis in the heterogeneous Cox model. Statistics in medicine, 40(3), 739-757, which has been published in final form at https://doi.org/10.1002/sim.8800. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited. | en_US |
dc.subject | Cox model | en_US |
dc.subject | Majorized ADMM algorithm | en_US |
dc.subject | Oracle property | en_US |
dc.subject | Subgroup analysis | en_US |
dc.subject | Treatment heterogeneity | en_US |
dc.title | Subgroup analysis in the heterogeneous Cox model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 739 | en_US |
dc.identifier.epage | 757 | en_US |
dc.identifier.volume | 40 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.1002/sim.8800 | en_US |
dcterms.abstract | In the analysis of censored survival data, to avoid a biased inference of treatment effects on the hazard function of the survival time, it is important to consider the treatment heterogeneity. Without requiring any prior knowledge about the subgroup structure, we propose a data driven subgroup analysis procedure for the heterogeneous Cox model by constructing a pairwise fusion penalized partial likelihood-based objective function. The proposed method can determine the number of subgroups, identify the group structure, and estimate the treatment effect simultaneously and automatically. A majorized alternating direction method of multipliers algorithm is then developed to deal with the numerically challenging high-dimensional problems. We also establish the oracle properties and the model selection consistency for the proposed penalized estimator. Our proposed method is evaluated by simulation studies and further illustrated by the analysis of the breast cancer data. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Statistics in medicine, 10 Feb. 2021, v. 40, no. 3, p. 739-757 | en_US |
dcterms.isPartOf | Statistics in medicine | en_US |
dcterms.issued | 2021-02-10 | - |
dc.identifier.scopus | 2-s2.0-85096661337 | - |
dc.identifier.pmid | 33169428 | - |
dc.identifier.eissn | 1097-0258 | en_US |
dc.description.validate | 202208 bcfc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | AMA-0074, a2342b | - |
dc.identifier.SubFormID | 47549 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 54170419 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Hu_Subgroup_Analysis_Heterogeneous.pdf | Pre-Published version | 431.75 kB | Adobe PDF | View/Open |
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