{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T20:31:00Z","timestamp":1775680260250,"version":"3.50.1"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T00:00:00Z","timestamp":1709510400000},"content-version":"vor","delay-in-days":42,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82173612"],"award-info":[{"award-number":["82173612"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82273730"],"award-info":[{"award-number":["82273730"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82073674"],"award-info":[{"award-number":["82073674"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82204163"],"award-info":[{"award-number":["82204163"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013105","name":"Shanghai Rising-Star Program","doi-asserted-by":"publisher","award":["21QA1401300"],"award-info":[{"award-number":["21QA1401300"]}],"id":[{"id":"10.13039\/501100013105","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Shanghai Municipal Natural Science Foundation","doi-asserted-by":"publisher","award":["22ZR1414900"],"award-info":[{"award-number":["22ZR1414900"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Municipal Science and Technology Major Project","award":["ZD2021CY001"],"award-info":[{"award-number":["ZD2021CY001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Recently, there has been a growing interest in variable selection for causal inference within the context of high-dimensional data. However, when the outcome exhibits a skewed distribution, ensuring the accuracy of variable selection and causal effect estimation might be challenging. Here, we introduce the generalized median adaptive lasso (GMAL) for covariate selection to achieve an accurate estimation of causal effect even when the outcome follows skewed distributions. A distinctive feature of our proposed method is that we utilize a linear median regression model for constructing penalty weights, thereby maintaining the accuracy of variable selection and causal effect estimation even when the outcome presents extremely skewed distributions. Simulation results showed that our proposed method performs comparably to existing methods in variable selection when the outcome follows a symmetric distribution. Besides, the proposed method exhibited obvious superiority over the existing methods when the outcome follows a skewed distribution. Meanwhile, our proposed method consistently outperformed the existing methods in causal estimation, as indicated by smaller root-mean-square error. We also utilized the GMAL method on a deoxyribonucleic acid methylation dataset from the Alzheimer\u2019s disease (AD) neuroimaging initiative database to investigate the association between cerebrospinal fluid tau protein levels and the severity of AD.<\/jats:p>","DOI":"10.1093\/bib\/bbae059","type":"journal-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T13:23:19Z","timestamp":1709558599000},"source":"Crossref","is-referenced-by-count":5,"title":["High-dimensional generalized median adaptive lasso with application to omics data"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1110-8183","authenticated-orcid":false,"given":"Yahang","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Health Statistics , School of Public Health, , Taiyuan , China"},{"name":"Shanxi Medical University , School of Public Health, , Taiyuan , China"},{"name":"Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kecheng","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ce","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongfu","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"},{"name":"Shanghai Institute of Infectious Disease and Biosecurity , Shanghai , China"},{"name":"Key Laboratory of Public Health Safety of Ministry of Education , Key Laboratory for Health Technology Assessment, National Commission of Health, , Shanghai , China"},{"name":"Fudan University , Key Laboratory for Health Technology Assessment, National Commission of Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoyou","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Biostatistics , School of Public Health, , Shanghai , China"},{"name":"Fudan University , School of Public Health, , Shanghai , China"},{"name":"Shanghai Institute of Infectious Disease and Biosecurity , Shanghai , China"},{"name":"Key Laboratory of Public Health Safety of Ministry of Education , Key Laboratory for Health Technology Assessment, National Commission of Health, , Shanghai , China"},{"name":"Fudan University , Key Laboratory for Health Technology Assessment, National Commission of Health, , Shanghai , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9403-7167","authenticated-orcid":false,"given":"Tong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Health Statistics , School of Public Health, , Taiyuan , China"},{"name":"Shanxi Medical 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