{"title":"A structural equation modeling approach for modeling variability as a latent variable.","authors":"Yi Feng, Gregory R Hancock","doi":"10.1037/met0000477","DOIUrl":null,"url":null,"abstract":"<p><p>Drawing upon recent developments in structural equation modeling, the current study presents an analytical framework for addressing research questions in which, rather than focusing on means, it is intraindividual (or intragroup) variability that is of direct research interest. Beyond merely serving as an alternative to existing multilevel modeling approaches, this framework allows for extensions to accommodate a variety of complex research scenarios by parameterizing variability as a latent variable that can in turn be embedded within a broader covariance and mean structure involving other observed and/or latent variables. The estimation procedures and parameter interpretation for the latent random variability models are discussed. The versatility of the proposed methods is demonstrated through four empirical examples. The Mplus, BUGS, and Stan model syntax for the illustrative examples are supplied to facilitate the application of the methods. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.6000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/met0000477","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/4/11 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Drawing upon recent developments in structural equation modeling, the current study presents an analytical framework for addressing research questions in which, rather than focusing on means, it is intraindividual (or intragroup) variability that is of direct research interest. Beyond merely serving as an alternative to existing multilevel modeling approaches, this framework allows for extensions to accommodate a variety of complex research scenarios by parameterizing variability as a latent variable that can in turn be embedded within a broader covariance and mean structure involving other observed and/or latent variables. The estimation procedures and parameter interpretation for the latent random variability models are discussed. The versatility of the proposed methods is demonstrated through four empirical examples. The Mplus, BUGS, and Stan model syntax for the illustrative examples are supplied to facilitate the application of the methods. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍：
Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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