{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T09:49:01Z","timestamp":1773308941354,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2020,6,17]],"date-time":"2020-06-17T00:00:00Z","timestamp":1592352000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,12,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>Left-truncation poses extra challenges for the analysis of complex time-to-event data. We propose a general semiparametric regression model for left-truncated and right-censored competing risks data that is based on a novel weighted conditional likelihood function. Targeting the subdistribution hazard, our parameter estimates are directly interpretable with regard to the cumulative incidence function. We compare different weights from recent literature and develop a heuristic interpretation from a cure model perspective that is based on pseudo risk sets. Our approach accommodates external time-dependent covariate effects on the subdistribution hazard. We establish consistency and asymptotic normality of the estimators and propose a sandwich estimator of the variance. In comprehensive simulation studies we demonstrate solid performance of the proposed method. Comparing the sandwich estimator with the inverse Fisher information matrix, we observe a bias for the inverse Fisher information matrix and diminished coverage probabilities in settings with a higher percentage of left-truncation. To illustrate the practical utility of the proposed method, we study its application to a large HIV vaccine efficacy trial dataset.<\/jats:p>","DOI":"10.1093\/biomet\/asaa034","type":"journal-article","created":{"date-parts":[[2020,4,15]],"date-time":"2020-04-15T19:19:54Z","timestamp":1586978394000},"page":"949-964","source":"Crossref","is-referenced-by-count":3,"title":["General regression model for the subdistribution of a competing risk under left-truncation and right-censoring"],"prefix":"10.1093","volume":"107","author":[{"given":"A","family":"Bellach","sequence":"first","affiliation":[{"name":"Department of Statistics, University of Washington, B313 Padelford Hall, NE Stevens Way, Seattle, Washington 98195, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M R","family":"Kosorok","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of North Carolina, 3101 McGavran\u2013Greenberg Hall, Chapel Hill, North Carolina 27599, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P B","family":"Gilbert","sequence":"additional","affiliation":[{"name":"Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N. Seattle,Washington 98109, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J P","family":"Fine","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of North Carolina, 3101 McGavran\u2013Greenberg Hall, Chapel Hill, North Carolina 27599, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,6,17]]},"reference":[{"key":"2020121116434292300_B1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1090\/conm\/080\/999006","article-title":"Censoring, truncation and filtering in statistical models based on counting processes","volume":"80","author":"Andersen,","year":"1988","journal-title":"Contemp. 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