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Direct linkJames 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
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
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
Fisk, Charles L.; Harring, Jeffrey R.; Shen, Zuchao; Leite, Walter; Suen, King Yiu; Marcoulides, Katerina M. – Educational and Psychological Measurement, 2023
Sensitivity analyses encompass a broad set of post-analytic techniques that are characterized as measuring the potential impact of any factor that has an effect on some output variables of a model. This research focuses on the utility of the simulated annealing algorithm to automatically identify path configurations and parameter values of omitted…
Descriptors: Structural Equation Models, Algorithms, Simulation, Evaluation Methods
Cox, Kyle; Kelcey, Benjamin – Educational and Psychological Measurement, 2023
Multilevel structural equation models (MSEMs) are well suited for educational research because they accommodate complex systems involving latent variables in multilevel settings. Estimation using Croon's bias-corrected factor score (BCFS) path estimation has recently been extended to MSEMs and demonstrated promise with limited sample sizes. This…
Descriptors: Structural Equation Models, Educational Research, Hierarchical Linear Modeling, Sample Size
Bogaert, Jasper; Loh, Wen Wei; Rosseel, Yves – Educational and Psychological Measurement, 2023
Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…
Descriptors: Factor Analysis, Regression (Statistics), Structural Equation Models, Error of Measurement
