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Analysis of such event time data can be biased if left\u2010truncation is not handled properly. We propose a semiparametric sieve likelihood approach for fitting a linear regression model to data where the response variable is subject to both left\u2010truncation and right\u2010censoring. We show that the estimators of regression coefficients are consistent, asymptotically normal and semiparametrically efficient. Extensive simulation studies show the effectiveness of the method across a wide variety of error distributions. We further illustrate the method by analyzing datasets from the Canadian Study of Health and Aging and The 90+ Study for aging and dementia.<\/jats:p>","DOI":"10.1002\/sim.70509","type":"journal-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T07:12:54Z","timestamp":1775113974000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Regression for Left\u2010Truncated and Right\u2010Censored Data: A Semiparametric Sieve Likelihood Approach"],"prefix":"10.1002","volume":"45","author":[{"given":"Spencer","family":"Matthews","sequence":"first","affiliation":[{"name":"Department of Statistics University of California  Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Nan","sequence":"additional","affiliation":[{"name":"Department of Statistics University of California  Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,2]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/ana.21915"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10463-020-00755-2"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781118032985"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2015.05.017"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177698883"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176346157"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176348110"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/0047-259X(92)90088-W"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176325627"},{"issue":"3","key":"e_1_2_11_11_1","first-page":"731","article-title":"Efficient Score Estimation and Adaptive M\u2010Estimators in Censored and Truncated Regression Models","volume":"10","author":"Kim C. 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