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Анализ на мощността за моделиране на структурни уравнения×Многовариантен анализ на дисперсията (MANOVA)×
ОбластСтатистикаСтатистика
СемействоHypothesis testHypothesis test
Година на възникване19961932
СъздателMacCallum, Browne & SugawaraSamuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
ТипSample size planning (multivariate / SEM)Parametric multivariate mean comparison
Основополагащ източникMacCallum, 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 ↗Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
Други названияSEM sample size planning, covariance structure power analysis, MANOVA power analysis, SEM / Çok Değişkenli Güç AnaliziMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
Свързани65
РезюмеPower 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.MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.
ScholarGateНабор от данни
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  3. PUBLISHED
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ScholarGateСравнение на методи: SEM Power Analysis · MANOVA. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare