{"data":{"id":"10.6084/m9.figshare.1632715","type":"dois","attributes":{"doi":"10.6084/m9.figshare.1632715","prefix":"10.6084","suffix":"m9.figshare.1632715","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Zhang, Yukun","givenName":"Yukun","familyName":"Zhang","affiliation":[],"nameIdentifiers":[]},{"name":"Lu, Xuewen","givenName":"Xuewen","familyName":"Lu","affiliation":[],"nameIdentifiers":[]},{"name":"F. Desmond, Anthony","givenName":"Anthony","familyName":"F. Desmond","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Variable Selection in a Log–Linear Birnbaum–Saunders Regression Model for High-Dimensional Survival Data via the Elastic-Net and Stochastic EM"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2016,"subjects":[{"subject":"Genetics"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Molecular Biology"},{"subject":"Biotechnology"},{"subject":"Evolutionary Biology"},{"subject":"Immunology"},{"subject":"FOS: Clinical medicine","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Information Systems not elsewhere classified"},{"subject":"Mathematical Sciences not elsewhere classified"},{"subject":"Cancer"},{"subject":"Inorganic Chemistry"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2016-07-08","dateType":"Created"},{"date":"2023-06-01","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/00401706.2015.1133457","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["232762 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The Birnbaum–Saunders (BS) distribution is broadly used to model failure times in reliability and survival analysis. In this article, we propose a simultaneous parameter estimation and variable selection procedure in a log–linear BS regression model for high-dimensional survival data. To deal with censored survival data, we iteratively run a combination of the stochastic EM algorithm (SEM) and variable selection procedure to generate pseudo-complete data and select variables until convergence. Treating pseudo-complete data as uncensored data via SEM makes it possible to incorporate iterative penalized least squares and simplify computation. We demonstrate the efficacy of our method using simulated and real 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