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Clark, D. Angus; Nuttall, Amy K.; Bowles, Ryan P. – International Journal of Behavioral Development, 2021
Hybrid autoregressive-latent growth structural equation models for longitudinal data represent a synthesis of the autoregressive and latent growth modeling frameworks. Although these models are conceptually powerful, in practice they may struggle to separate autoregressive and growth-related processes during estimation. This confounding of change…
Descriptors: Structural Equation Models, Longitudinal Studies, Risk, Accuracy
Clark, D. Angus; Bowles, Ryan P. – Grantee Submission, 2018
In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present…
Descriptors: Factor Analysis, Goodness of Fit, Factor Structure, Monte Carlo Methods