Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93917
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Yan, X | en_US |
dc.creator | Yin, G | en_US |
dc.creator | Zhao, X | en_US |
dc.date.accessioned | 2022-08-03T01:24:12Z | - |
dc.date.available | 2022-08-03T01:24:12Z | - |
dc.identifier.issn | 1017-0405 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93917 | - |
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.rights | The following publication Yan, X., Yin, G. and Zhao, X*. (2021). Subgroup analysis in censored linear regression, Statistica Sinica 31, 1027-1054 is available at https://dx.doi.org/10.5705/ss.202018.0319. | en_US |
dc.subject | Concave penalization | en_US |
dc.subject | Oracle property | en_US |
dc.subject | Subgroup analysis | en_US |
dc.subject | Survival data | en_US |
dc.subject | Treatment heterogeneity | en_US |
dc.title | Subgroup analysis in censored linear regression | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1027 | en_US |
dc.identifier.epage | 1054 | en_US |
dc.identifier.volume | 31 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.doi | 10.5705/ss.202018.0319 | en_US |
dcterms.abstract | In the presence of treatment heterogeneity due to unknown grouping information, standard methods that assume homogeneous treatment effiects cannot capture the subgroup structure in the population. To accommodate such heterogeneity, we propose a concave fusion approach to identifying the subgroup structures and estimating the treatment effiects for a semiparametric linear regression with censored data. In particular, the treatment effiects are subject-dependent and subgroup-specific, and our concave fusion penalized method conducts the subgroup analysis without needing to know the individual subgroup memberships in advance. The proposed estimation procedure automatically identifies the subgroup structure and simultaneously estimates the subgroup-specific treatment effiects. The proposed algorithm combines the Buckley{James iterative procedure and the alternating direction method of multipliers. The resulting estimators enjoy the oracle property, and simulation studies and a real-data application demonstrate the good performance of the proposed method. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Statistica sinica, Apr. 2021, v. 31, no. 2, p. 1027-1054 | en_US |
dcterms.isPartOf | Statistica sinica | en_US |
dcterms.issued | 2021-04 | - |
dc.identifier.scopus | 2-s2.0-85100217034 | - |
dc.description.validate | 202208 bcfc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | AMA-0061, a2342b | - |
dc.identifier.SubFormID | 47547 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 54170017 | - |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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A31n220.pdf | 978.99 kB | Adobe PDF | View/Open |
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