{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:13:08Z","timestamp":1760058788096,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T00:00:00Z","timestamp":1745971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71873128"],"award-info":[{"award-number":["71873128"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>In this paper, we propose a new variable selection method using a partitioning-based estimating equation for multivariate survival data to simultaneously perform variable selection and parameter estimation. The main idea of the partitioning-based estimating equation is to partition the score function into small blocks. We construct our method using the SCAD penalty function and achieve the purpose of directly selecting variables through the estimating equation. We further establish asymptotic normality and prove that our method achieves the oracle property. Moreover, we use a simple approximation of the penalty function such that our method can be implemented algorithmically. We conducted simulation studies to validate the performance of our method and analyzed the dataset from the Colon Cancer Study.<\/jats:p>","DOI":"10.3390\/axioms14050348","type":"journal-article","created":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T09:16:12Z","timestamp":1746090972000},"page":"348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Partitioning-Based Approach to Variable Selection in WLW Model for Multivariate Survival Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Wenjian","family":"Tian","sequence":"first","affiliation":[{"name":"Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China"}]},{"given":"Wenquan","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1111\/j.2517-6161.1993.tb01914.x","article-title":"Modelling marginal hazards in multivariate failure time data","volume":"55","author":"Liang","year":"1993","journal-title":"J. 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