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SEM Power Analysis

Power analysis for SEM and other multivariate procedures determines the minimum sample size required to detect a model misfit of a specified magnitude with adequate probability. The dominant approach, introduced by MacCallum, Browne, and Sugawara in 1996, expresses effect size as the Root Mean Square Error of Approximation (RMSEA) and derives power from the noncentral chi-square distribution.

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Power Analysis for Structural Equation Modeling and Multivariate Analyses

Taksonoomiline meetodikirje · hypothesis-test / statistics

MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. · DOI 10.1037/1082-989X.1.2.130

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Same method familyMANOVAmachine-suggested · Relational suggestion, not evidence.Same method familyMultilevel Power Analysismachine-suggested · Relational suggestion, not evidence.Same method familyPower Analysis for ANOVAmachine-suggested · Relational suggestion, not evidence.Same method familyPower Analysis for Regressionmachine-suggested · Relational suggestion, not evidence.Same method familySimulation-Based Power Analysismachine-suggested · Relational suggestion, not evidence.See alsoStructural Equation Modelingmachine-suggested · Relational suggestion, not evidence.