James L. Peugh, Michael D. Toland, Heather Harrison
{"title":"A Tutorial for Handling Suspected Missing Not at Random Data in Longitudinal Clinical Trials","authors":"James L. Peugh, Michael D. Toland, Heather Harrison","doi":"10.20982/tqmp.19.4.p347","DOIUrl":null,"url":null,"abstract":"Missing data in longitudinal randomized clinical trials, even if assumed to be missing at random (MAR), can result in biased parameter estimates and incorrect treatment conclusions. If missing data are suspected to be missing not at random (MNAR, i","PeriodicalId":93055,"journal":{"name":"The quantitative methods for psychology","volume":" 29","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The quantitative methods for psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20982/tqmp.19.4.p347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Missing data in longitudinal randomized clinical trials, even if assumed to be missing at random (MAR), can result in biased parameter estimates and incorrect treatment conclusions. If missing data are suspected to be missing not at random (MNAR, i