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SEM Power Analysis/Evidence
Method evidence record

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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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Power Analysis for Structural Equation Modeling and Multivariate Analyses
Taxonomic method record · 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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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

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.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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