{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:09:44Z","timestamp":1764842984351,"version":"3.41.2"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T00:00:00Z","timestamp":1736208000000},"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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12301367"],"award-info":[{"award-number":["12301367"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,1,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n               <jats:p>The segmented model has significant applications in scientific research when the change-point effect exists. In this article, we propose a comprehensive semiparametric framework in segmented models to test the existence and estimate the location of change points in the generalized outcome setting. The proposed framework is based on a semismooth estimating equation\u00a0for the change-point estimation and an average score-type test for hypothesis testing. The root-n consistency, asymptotic normality, and asymptotic efficiency of estimators for all parameters in the segmented model are rigorously studied. The distribution of the average score-type test statistics under the null hypothesis is rigorously derived. Extensive simulation studies are conducted to assess the numerical performance of the proposed change-point estimation method and the average score-type test. We investigate change-point effects of baseline glomerular filtration rate and body mass index on bleeding after intervention using data from Blue Cross Blue Shield. This application study successfully identifies statistically significant change-point effects, with the estimated values providing clinically meaningful insights.<\/jats:p>","DOI":"10.1093\/biomtc\/ujaf022","type":"journal-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T14:36:21Z","timestamp":1741790181000},"source":"Crossref","is-referenced-by-count":2,"title":["Statistical inference on change points in generalized semiparametric segmented models"],"prefix":"10.1093","volume":"81","author":[{"given":"Guangyu","family":"Yang","sequence":"first","affiliation":[{"name":"Institute of Statistics and Big Data, Renmin University of China , Beijing, 100872 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baqun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Statistics and Management, Shanghai University of Finance and Economics , Shanghai, 200433 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