Adam Garber
· LecturerVerifiedUniversity of California, Santa Barbara · Environmental Science and Management
Active 2020–2022
Research signals
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Research topics
- Computer Science
- Machine Learning
- Psychology
- Clinical psychology
- Psychotherapist
- Social psychology
- Mathematics
- Sociology
- Econometrics
- Environmental health
- Psychiatry
- Developmental psychology
- Medicine
Selected publications
Behavioral Disorders · 2022 · 61 citations
- Computer Science
- Machine Learning
- Psychology
Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This article provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youths’ daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of the LCA variable within a structural equation model framework, specifically a latent class moderation model, and a detailed table provides a summary of relevant modeling steps. This applied example demonstrates the modeling context when the LCA variable is moderating the association between a covariate and two outcome variables. Results indicate that students’ coping strategies moderate the association between social stress and negative mood; however, they do not moderate the social stress-positive mood association. Online supplemental materials include R (MplusAutomation) code to automate the enumeration procedure, ML three-step auxiliary variable integration, and the generation of figures for visually depicting LCA results.
2021 · 4 citations
- Computer Science
- Machine Learning
- Psychology
Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This paper provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youth’s daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of the LCA variable within a structural equation model framework, specifically a latent class moderation model, and a detailed table provides a summary of relevant modeling steps. This applied example demonstrates the modeling context when the LCA variable is moderating the association between a covariate and two outcome variables. Results indicate that students’ coping strategies moderate the association between social stress and negative mood, however they do not moderate the social stress-positive mood association. Appendices include R (MplusAutomation) code to automate the enumeration procedure, 3-step auxiliary variable integration, and the generation of figures for visually depicting LCA results.
Journal of Abnormal Child Psychology · 2020 · 40 citations
Senior authorCorresponding- Psychology
- Clinical psychology
- Developmental psychology
Frequent coauthors
- 5 shared
Karen Nylund‐Gibson
University of California, Santa Barbara
- 2 shared
Delwin Carter
University of California, Santa Barbara
- 2 shared
Adrienne Nishina
University of California, Davis
- 2 shared
Mei‐ki Chan
- 2 shared
Melissa R. Witkow
- 2 shared
Jay P. Singh
University of Konstanz
- 2 shared
Amy Bellmore
University of Wisconsin–Madison
- 2 shared
Dina A. N. Arch
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