{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T23:31:24Z","timestamp":1780097484067,"version":"3.54.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T00:00:00Z","timestamp":1707782400000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Nature Science Foundation of Guangdong Province of China"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>Group testing is an effective way to reduce the time and cost associated with conducting large-scale screening for infectious diseases. Benefits are realized through testing pools formed by combining specimens, such as blood or urine, from different individuals. In some studies, individuals are assessed only once and a time-to-event endpoint is recorded, for example, the time until infection. Combining group testing with this type of endpoint results in group-tested current status data (Petito &amp; Jewell, 2016). To analyse these complex data, we propose methods that estimate a proportional hazard regression model based on test outcomes from measuring the pools. A sieve maximum likelihood estimation approach is developed that approximates the cumulative baseline hazard function with a piecewise constant function. To identify the sieve estimator, a computationally efficient expectation-maximization algorithm is derived by using data augmentation. Asymptotic properties of both the parametric and nonparametric components of the sieve estimator are then established by applying modern empirical process theory. Numerical results from simulation studies show that our proposed method performs nominally and has advantages over the corresponding estimation method based on individual testing results. We illustrate our work by analysing a chlamydia dataset collected by the State Hygienic Laboratory at the University of Iowa.<\/jats:p>","DOI":"10.1093\/biomet\/asae006","type":"journal-article","created":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T00:49:44Z","timestamp":1707785384000},"page":"1047-1061","source":"Crossref","is-referenced-by-count":5,"title":["Regression analysis of group-tested current status data"],"prefix":"10.1093","volume":"111","author":[{"given":"Shuwei","family":"Li","sequence":"first","affiliation":[{"name":"School of Economics and Statistics, Guangzhou University , Daxuecheng Road 230, Guangzhou, Guangdong 510006,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4463-004X","authenticated-orcid":false,"given":"Tao","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Capital Normal University , Beijing 100048,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianming","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of South Carolina, 209A LeConte College , Columbia, South Carolina 29208,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher S","family":"McMahan","sequence":"additional","affiliation":[{"name":"School of Mathematical and Statistical Sciences, Clemson University , Martin Hall, Clemson, South Carolina 29634,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6762-7241","authenticated-orcid":false,"given":"Joshua M","family":"Tebbs","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of South Carolina , 217 LeConte College, Columbia, South Carolina 29208,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"2025021201205296900_asae006-B1","first-page":"715","article-title":"Assessment of specimen pooling to conserve SARS CoV-2 testing resources","volume":"153","author":"Abdalhamid","year":"2020","journal-title":"Am. 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