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James Ohisei Uanhoro – Educational and Psychological Measurement, 2024
Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…
Descriptors: Bayesian Statistics, Structural Equation Models, Simulation, Statistical Inference
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W. Holmes Finch – Educational and Psychological Measurement, 2024
Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…
Descriptors: Models, Regression (Statistics), Structural Equation Models, Predictor Variables
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Ulrich Schroeders; Florian Scharf; Gabriel Olaru – Educational and Psychological Measurement, 2024
Metaheuristics are optimization algorithms that efficiently solve a variety of complex combinatorial problems. In psychological research, metaheuristics have been applied in short-scale construction and model specification search. In the present study, we propose a bee swarm optimization (BSO) algorithm to explore the structure underlying a…
Descriptors: Structural Equation Models, Heuristics, Algorithms, Measurement Techniques