Using Dynamic Structural Equation Modeling to Examine Between- and Within-Persons Factor Structure of the DASS-21

Melissa H. Bond, Robert E. Wickham

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The recent integration of traditional time series analysis and confirmatory factor analysis techniques allows researchers to evaluate the psychometric properties of measurement instruments at between- and within-persons levels while accounting for autoregressive dependencies. The current study applies a dynamic structural equation modeling (SEM) latent factor analysis (i.e., DSEM-CFA) to a sample of 333 individuals who completed the DASS-21 at their regular therapy sessions. The results of the DSEM-CFA illuminate the reliability, invariance, and structural features of each DASS-21 subscale both between and within persons. The results suggest that the DASS-21 reliably measures depression, anxiety, and stress symptoms when evaluating differences between persons, but does not reliably assess within-persons fluctuations in symptoms over time. The results also suggest that currently accepted methods of modeling sensitivity to change within an instrument are likely lacking and the DSEM-CFA provides insight into reliability within and between persons, which is extremely important for instruments used across time.

Original languageEnglish (US)
Pages (from-to)2115-2127
Number of pages13
JournalAssessment
Volume30
Issue number7
DOIs
StatePublished - Oct 2023

Keywords

  • dynamic SEM
  • factor analysis
  • multilevel
  • psychometrics
  • time series

ASJC Scopus subject areas

  • Clinical Psychology
  • Applied Psychology

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