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Nova · Professor Researcher · re-ranking top 20…

Adam Garber

· LecturerVerified

University of California, Santa Barbara · Environmental Science and Management

Active 2020–2022

h-index4
Citations158
Papers99 last 5y
Funding
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Research signals

Five dimensions sourced from public faculty / publication signals. Sign in to compare against your own profile and see your match score.

Research topics

  • Computer Science
  • Machine Learning
  • Psychology
  • Clinical psychology
  • Psychotherapist
  • Social psychology
  • Mathematics
  • Sociology
  • Econometrics
  • Environmental health
  • Psychiatry
  • Developmental psychology
  • Medicine

Selected publications

  • The Utility of Latent Class Analysis to Understand Heterogeneity in Youth Coping Strategies: A Methodological Introduction

    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.

  • The Utility of Latent Class Analysis to Understand Heterogeneity in Youth’s Coping Strategies: A Methodological Introduction

    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.

  • Why Family Communication Matters: the Role of Co-rumination and Topic Avoidance in Understanding Post-Disaster Mental Health

    Journal of Abnormal Child Psychology · 2020 · 40 citations

    Senior authorCorresponding
    • Psychology
    • Clinical psychology
    • Developmental psychology

Frequent coauthors

  • Karen Nylund‐Gibson

    University of California, Santa Barbara

    5 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

    2 shared

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