{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T06:51:50Z","timestamp":1791355910927,"version":"4.3.1"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2012,4,16]],"date-time":"2012-04-16T00:00:00Z","timestamp":1334534400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biometrics"],"published-print":{"date-parts":[[2012,6]]},"abstract":"<jats:p><jats:bold><jats:sc>Summary<\/jats:sc><\/jats:bold>Cox models with time\u2010varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right\u2010censored failure times. Because not all covariate coefficients are time varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time\u2010varying coefficient from those with time\u2010independent coefficient. We propose an adaptive group lasso method that not only selects important variables but also selects between time\u2010independent and time\u2010varying specifications of their presence in the model. Each covariate effect is partitioned into a time\u2010independent part and a time\u2010varying part, the latter of which is characterized by a group of coefficients of basis splines without intercept. Model selection and estimation are carried out through a fast, iterative group shooting algorithm. Our approach is shown to have good properties in a simulation study that mimics realistic situations with up to 20 variables. A real example illustrates the utility of the method.<\/jats:p>","DOI":"10.1111\/j.1541-0420.2011.01692.x","type":"journal-article","created":{"date-parts":[[2012,4,16]],"date-time":"2012-04-16T20:39:12Z","timestamp":1334608752000},"page":"419-428","source":"Crossref","is-referenced-by-count":46,"title":["Model Selection for Cox Models with Time\u2010Varying Coefficients"],"prefix":"10.1093","volume":"68","author":[{"given":"Jun","family":"Yan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2012,4,16]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.4310\/SII.2009.v2.n3.a10"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOAS388"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9469.00320"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01404567"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382273"},{"key":"e_1_2_9_7_1","first-page":"74","article-title":"Variable selection for Cox\u2019s proportional hazards model and frailty model","volume":"30","author":"Fan J.","year":"2002","journal-title":"The Annals of Statistics"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/996986505"},{"key":"e_1_2_9_9_1","volume-title":"Counting Processes and Survival Analysis","author":"Fleming T. 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