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… Click to show full 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.
               
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