{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T10:09:35Z","timestamp":1753870175224,"version":"3.41.2"},"reference-count":38,"publisher":"Wiley","issue":"10-12","license":[{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"vor","delay-in-days":18,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>The case\u2010cohort design is a valuable two\u2010phase sampling scheme often used in situations with low disease incidence and challenges in obtaining covariate data due to cost constraints, and many methods have been proposed for its analysis. However, most of the existing approaches, particularly for interval\u2010censored data, ignore the presence of non\u2010expensive covariates that are typically observed for the entire cohort and thus can result in the significant loss of efficiency. To address this, under the framework of the semi\u2010parametric transformation hazards model, we propose a supersampling approach that augments the case\u2010cohort samples by introducing an additional sub\u2010cohort, allowing us to incorporate non\u2010expensive covariates. In the proposed method, the multiple imputation procedure is employed based on rejection sampling, and the asymptotic properties of the resulting estimator of regression parameters are established. To evaluate the finite sample performance of the proposed method, a simulation study is conducted, and it demonstrates its effectiveness in practical situations. Finally, the proposed methodology is applied to an HIV vaccine trial that motivated this study.<\/jats:p>","DOI":"10.1002\/sim.70115","type":"journal-article","created":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T11:31:05Z","timestamp":1747654265000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Augmented Approach for Regression Analysis of Case\u2010Cohort Interval\u2010Censored Failure Time Data"],"prefix":"10.1002","volume":"44","author":[{"given":"Yichen","family":"Lou","sequence":"first","affiliation":[{"name":"Department of Statistics The Chinese University of Hong Kong  Hong Kong Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingyue","family":"Du","sequence":"additional","affiliation":[{"name":"School of Mathematics Jilin University  Changchun China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3579-7916","authenticated-orcid":false,"given":"Peijie","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mathematics Jilin University  Changchun China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Statistics University of Missouri  Columbia Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,5,19]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/73.1.1"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176350691"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/86.4.755"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/93.1.207"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asp059"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/ast018"},{"volume-title":"The Statistical Analysis of Interval\u2010Censored Failure Time Data","year":"2006","author":"Sun J.","key":"e_1_2_10_8_1"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-12366-5"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1086\/428405"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1310566"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/infdis\/jix086"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/infdis\/jiy008"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asw067"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/sta4.70025"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1080\/02664763.2020.1752633"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40304-022-00322-6"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/cjs.11818"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.8962"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10985-023-09593-9"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610926.2023.2220850"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201900180"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2022.107484"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1177\/0962280214521348"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4130"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5818"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6588"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12910"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1111\/sjos.12624"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/9780470316696"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7816"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1997.10474050"},{"key":"e_1_2_10_33_1","doi-asserted-by":"publisher","DOI":"10.1201\/b12290"},{"key":"e_1_2_10_34_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/85.4.935"},{"key":"e_1_2_10_35_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/87.1.113"},{"volume-title":"Semiparametric Theory and Missing Data","year":"2006","author":"Tsiatis A. 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