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- Publisher Website: 10.1080/01621459.2019.1602047
- Scopus: eid_2-s2.0-85087063767
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Article: Functional Censored Quantile Regression
Title | Functional Censored Quantile Regression |
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Authors | |
Keywords | B-spline Censored quantile regression Functional regression Generalized approximate cross-validation Time-varying effect |
Issue Date | 2020 |
Publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main |
Citation | Journal of the American Statistical Association, 2020, v. 115 n. 530, p. 931-944 How to Cite? |
Abstract | We propose a functional censored quantile regression model to describe the time-varying relationship between time-to-event outcomes and corresponding functional covariates. The time-varying effect is modeled as an unspecified function that is approximated via B-splines. A generalized approximate cross-validation method is developed to select the number of knots by minimizing the expected loss. We establish asymptotic properties of the method and the knot selection procedure. Furthermore, we conduct extensive simulation studies to evaluate the finite sample performance of our method. Finally, we analyze the functional relationship between ambulatory blood pressure trajectories and clinical outcome in stroke patients. The results reinforce the importance of the morning blood pressure surge phenomenon, whose effect has caught attention but remains controversial in the medical literature. Supplementary materials for this article are available online. |
Persistent Identifier | http://hdl.handle.net/10722/278923 |
ISSN | 2023 Impact Factor: 3.0 2023 SCImago Journal Rankings: 3.922 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Jiang, F | - |
dc.contributor.author | Cheng, Q | - |
dc.contributor.author | Yin, G | - |
dc.contributor.author | Shen, H | - |
dc.date.accessioned | 2019-10-21T02:16:24Z | - |
dc.date.available | 2019-10-21T02:16:24Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Journal of the American Statistical Association, 2020, v. 115 n. 530, p. 931-944 | - |
dc.identifier.issn | 0162-1459 | - |
dc.identifier.uri | http://hdl.handle.net/10722/278923 | - |
dc.description.abstract | We propose a functional censored quantile regression model to describe the time-varying relationship between time-to-event outcomes and corresponding functional covariates. The time-varying effect is modeled as an unspecified function that is approximated via B-splines. A generalized approximate cross-validation method is developed to select the number of knots by minimizing the expected loss. We establish asymptotic properties of the method and the knot selection procedure. Furthermore, we conduct extensive simulation studies to evaluate the finite sample performance of our method. Finally, we analyze the functional relationship between ambulatory blood pressure trajectories and clinical outcome in stroke patients. The results reinforce the importance of the morning blood pressure surge phenomenon, whose effect has caught attention but remains controversial in the medical literature. Supplementary materials for this article are available online. | - |
dc.language | eng | - |
dc.publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main | - |
dc.relation.ispartof | Journal of the American Statistical Association | - |
dc.rights | AOM/Preprint Before Accepted: his article has been accepted for publication in [JOURNAL TITLE], published by Taylor & Francis. AOM/Preprint After Accepted: This is an [original manuscript / preprint] of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI]. Accepted Manuscript (AM) i.e. Postprint This is an Accepted Manuscript of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI]. | - |
dc.subject | B-spline | - |
dc.subject | Censored quantile regression | - |
dc.subject | Functional regression | - |
dc.subject | Generalized approximate cross-validation | - |
dc.subject | Time-varying effect | - |
dc.title | Functional Censored Quantile Regression | - |
dc.type | Article | - |
dc.identifier.email | Jiang, F: feijiang@hku.hk | - |
dc.identifier.email | Yin, G: gyin@hku.hk | - |
dc.identifier.email | Shen, H: haipeng@hku.hk | - |
dc.identifier.authority | Jiang, F=rp02185 | - |
dc.identifier.authority | Yin, G=rp00831 | - |
dc.identifier.authority | Shen, H=rp02082 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/01621459.2019.1602047 | - |
dc.identifier.scopus | eid_2-s2.0-85087063767 | - |
dc.identifier.hkuros | 308037 | - |
dc.identifier.volume | 115 | - |
dc.identifier.issue | 530 | - |
dc.identifier.spage | 931 | - |
dc.identifier.epage | 944 | - |
dc.identifier.isi | WOS:000470485900001 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0162-1459 | - |