{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:35:42Z","timestamp":1787506542393,"version":"build-2736575974"},"reference-count":47,"publisher":"Wiley","issue":"24","license":[{"start":{"date-parts":[[2013,5,10]],"date-time":"2013-05-10T00:00:00Z","timestamp":1368144000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2013,5,10]],"date-time":"2013-05-10T00:00:00Z","timestamp":1368144000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"},{"start":{"date-parts":[[2013,5,10]],"date-time":"2013-05-10T00:00:00Z","timestamp":1368144000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001868","name":"National Science Council, Taiwan","doi-asserted-by":"crossref","award":["NSC85-2121-M-001-002"],"award-info":[{"award-number":["NSC85-2121-M-001-002"]}],"id":[{"id":"10.13039\/501100001868","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001868","name":"National Science Council, Taiwan","doi-asserted-by":"crossref","award":["NSC101-2325-B-002-078"],"award-info":[{"award-number":["NSC101-2325-B-002-078"]}],"id":[{"id":"10.13039\/501100001868","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004737","name":"National Health Research Institutes, Taiwan","doi-asserted-by":"crossref","award":["NHRI-EX94-9225PP"],"award-info":[{"award-number":["NHRI-EX94-9225PP"]}],"id":[{"id":"10.13039\/501100004737","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2013,10,30]]},"abstract":"<jats:p>In conventional survival analysis there is an underlying assumption that all study subjects are susceptible to the event. In general, this assumption does not adequately hold when investigating the time to an event other than death. Owing to genetic and\/or environmental etiology, study subjects may not be susceptible to the disease. Analyzing nonsusceptibility has become an important topic in biomedical, epidemiological, and sociological research, with recent statistical studies proposing several mixture models for right\u2010censored data in regression analysis. In longitudinal studies, we often encounter left, interval, and right\u2010censored data because of incomplete observations of the time endpoint, as well as possibly left\u2010truncated data arising from the dissimilar entry ages of recruited healthy subjects. To analyze these kinds of incomplete data while accounting for nonsusceptibility and possible crossing hazards in the framework of mixture regression models, we utilize a logistic regression model to specify the probability of susceptibility, and a generalized gamma distribution, or a log\u2010logistic distribution, in the accelerated failure time location\u2010scale regression model to formulate the time to the event. Relative times of the conditional event time distribution for susceptible subjects are extended in the accelerated failure time location\u2010scale submodel. We also construct graphical goodness\u2010of\u2010fit procedures on the basis of the Turnbull\u2013Frydman estimator and newly proposed residuals. Simulation studies were conducted to demonstrate the validity of the proposed estimation procedure. The mixture regression models are illustrated with alcohol abuse data from the Taiwan Aboriginal Study Project and hypertriglyceridemia data from the Cardiovascular Disease Risk Factor Two\u2010township Study in Taiwan. Copyright \u00a9 2013 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.5845","type":"journal-article","created":{"date-parts":[[2013,5,10]],"date-time":"2013-05-10T01:42:52Z","timestamp":1368150172000},"page":"4285-4305","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Logistic\u2010AFT location\u2010scale mixture regression models with nonsusceptibility for left\u2010truncated and general interval\u2010censored data"],"prefix":"10.1002","volume":"32","author":[{"given":"Chen\u2010Hsin","family":"Chen","sequence":"first","affiliation":[{"name":"Institute of Statistical Science Academia Sinica Taipei 11529 Taiwan"},{"name":"Graduate Institute of Epidemiology and Preventive Medicine National Taiwan University Taipei 10055 Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuh\u2010Chyuan","family":"Tsay","sequence":"additional","affiliation":[{"name":"Institute of Statistical Science 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