{"title":"A comparison of three approaches for identifying correlates of heterogeneity in change.","authors":"Sarfaraz Serang","doi":"10.1002/cad.20390","DOIUrl":null,"url":null,"abstract":"<p><p>Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures heterogeneity, attributes that heterogeneity to covariates, and the kinds of research questions each can be used to address. Each approach is used to analyze data from the National Longitudinal Survey of Youth to understand the similarities and differences between methods in the context of empirical data. Specifically, changes in weight across adolescence are examined, as well as how differences in these change patterns can be explained by sex, race, and mother's education. Recommendations are provided for how to select which approach is most appropriate for analyzing one's own data.</p>","PeriodicalId":47745,"journal":{"name":"New Directions for Child and Adolescent Development","volume":"2021 175","pages":"141-160"},"PeriodicalIF":3.4000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cad.20390","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Directions for Child and Adolescent Development","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1002/cad.20390","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/17 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, DEVELOPMENTAL","Score":null,"Total":0}
引用次数: 2
Abstract
Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures heterogeneity, attributes that heterogeneity to covariates, and the kinds of research questions each can be used to address. Each approach is used to analyze data from the National Longitudinal Survey of Youth to understand the similarities and differences between methods in the context of empirical data. Specifically, changes in weight across adolescence are examined, as well as how differences in these change patterns can be explained by sex, race, and mother's education. Recommendations are provided for how to select which approach is most appropriate for analyzing one's own data.
期刊介绍:
The mission of New Directions for Child and Adolescent Development is to provide scientific and scholarly presentations on cutting edge issues and concepts in the field of child and adolescent development. Each issue focuses on a specific new direction or research topic, and is peer reviewed by experts on that topic. Any topic in the domain of child and adolescent development can be the focus of an issue. Topics can include social, cognitive, educational, emotional, biological, neuroscience, health, demographic, economical, and socio-cultural issues that bear on children and youth, as well as issues in research methodology and other domains. Topics that bridge across areas are encouraged, as well as those that are international in focus or deal with under-represented groups. The readership for the journal is primarily students, researchers, scholars, and social servants from fields such as psychology, sociology, education, social work, anthropology, neuroscience, and health. We welcome scholars with diverse methodological and epistemological orientations.