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Psychometric Properties of the Adult Self-Report: Data from over 11,000 American Adults

Author

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  • Michelle Guerrero

    (Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada)

  • Matt Hoffmann

    (Department of Kinesiology, California State University, Fullerton, CA 92831, USA)

  • Laura Pulkki-Råback

    (Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, 00100 Helsinki, Finland
    Department of Clinical Medicine, Division of Child Psychiatry, University of Turku, 20014 Turku, Finland)

Abstract

The first purpose of this study was to examine the factor structure of the Adult Self-Report (ASR) via traditional confirmatory factor analysis (CFA) and contemporary exploratory structural equation modeling (ESEM). The second purpose was to examine the measurement invariance of the ASR subscales across age groups. We used baseline data from the Adolescent Brain Cognitive Development study. ASR data from 11,773 participants were used to conduct the CFA and ESEM analyses and data from 11,678 participants were used to conduct measurement invariance testing. Fit indices supported both the CFA and ESEM solutions, with the ESEM solution yielding better fit indices. However, several items in the ESEM solution did not sufficiently load on their intended factors and/or cross-loaded on unintended factors. Results from the measurement invariance analysis suggested that the ASR subscales are robust and fully invariant across subgroups of adults formed on the basis of age (18–35 years vs. 36–59 years). Future research should seek to both CFA and ESEM to provide a more comprehensive assessment of the ASR.

Suggested Citation

  • Michelle Guerrero & Matt Hoffmann & Laura Pulkki-Råback, 2020. "Psychometric Properties of the Adult Self-Report: Data from over 11,000 American Adults," Stats, MDPI, vol. 3(4), pages 1-10, October.
    • Handle: RePEc:gam:jstats:v:3:y:2020:i:4:p:29-474:d:436517
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    References listed on IDEAS

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    1. Mohsen Joshanloo & Paul E. Jose & Magdalena Kielpikowski, 2017. "The Value of Exploratory Structural Equation Modeling in Identifying Factor Overlap in the Mental Health Continuum-Short Form (MHC-SF): A Study with a New Zealand Sample," Journal of Happiness Studies, Springer, vol. 18(4), pages 1061-1074, August.
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