Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93920
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Chai, H | en_US |
dc.creator | Zhang, Q | en_US |
dc.creator | Huang, J | en_US |
dc.creator | Ma, S | en_US |
dc.date.accessioned | 2022-08-03T01:24:13Z | - |
dc.date.available | 2022-08-03T01:24:13Z | - |
dc.identifier.issn | 1017-0405 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93920 | - |
dc.language.iso | en | en_US |
dc.publisher | Academia Sinica, Institute of Statistical Science | en_US |
dc.rights | Posted with permission of the publisher. | en_US |
dc.subject | AFT model | en_US |
dc.subject | Censored survival data | en_US |
dc.subject | High-dimensional inference | en_US |
dc.title | Inference for low-dimensional covariates in a high-dimensional accelerated failure time model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 877 | en_US |
dc.identifier.epage | 894 | en_US |
dc.identifier.volume | 29 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.doi | 10.5705/ss.202016.0449 | en_US |
dcterms.abstract | Data with high-dimensional covariates are now commonly encountered. Compared to other types of responses, research on high-dimensional data with censored survival responses is still relatively limited, and most of the existing studies have been focused on estimation and variable selection. In this study, we consider data with a censored survival response, a set of low-dimensional covariates of main interest, and a set of high-dimensional covariates that may also affect survival. The accelerated failure time model is adopted to describe survival. The goal is to conduct inference for the effects of low-dimensional covariates, while properly accounting for the high-dimensional covariates. A penalization-based procedure is developed, and its validity is established under mild and widely adopted conditions. Simulation suggests satisfactory performance of the proposed procedure, and the analysis of two cancer genetic datasets demonstrates its practical applicability. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Statistica sinica, Apr. 2019, v. 29, no. 2, p. 877-894 | en_US |
dcterms.isPartOf | Statistica sinica | en_US |
dcterms.issued | 2019-04 | - |
dc.identifier.scopus | 2-s2.0-85065243640 | - |
dc.description.validate | 202208 bcfc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | AMA-0318 | - |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 14478342 | - |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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A29n216.pdf | 348.88 kB | Adobe PDF | View/Open |
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