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Direct linkEunsook Kim; Diep Nguyen; Siyu Liu; Yan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Factor mixture modeling (FMM) is generally complex with both unobserved categorical and unobserved continuous variables. We explore the potential of item parceling to reduce the model complexity of FMM and improve convergence and class enumeration accordingly. To this end, we conduct Monte Carlo simulations with three types of data, continuous,…
Descriptors: Structural Equation Models, Factor Analysis, Factor Structure, Monte Carlo Methods
Wang, Zhongmiao; Thompson, Bruce – Journal of Experimental Education, 2007
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R[squared] correction formulas with the Pearson r[squared]. The authors estimated adjustment bias and precision under 6 x 3 x 6 conditions (i.e., population [rho] values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9; population shapes normal, skewness…
Descriptors: Effect Size, Correlation, Mathematical Formulas, Monte Carlo Methods
