So sánh phương pháp

	Phân tích lực cho Mô hình Cấu trúc Tuyến tính	Phân tích công suất cho hồi quy đa biến
Lĩnh vực	Thống kê	Thống kê
Họ	Hypothesis test	Hypothesis test
Năm ra đời	1996	1988
Người khởi xướng	MacCallum, Browne & Sugawara	Jacob Cohen
Loại	Sample size planning (multivariate / SEM)	A priori sample size determination
Công trình gốc	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.	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Tên gọi khác	SEM sample size planning, covariance structure power analysis, MANOVA power analysis, SEM / Çok Değişkenli Güç Analizi	regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon
Liên quan	6	4
Tóm tắt	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.	Power analysis for multiple regression is a pre-study procedure, formalised by Jacob Cohen (1988), that calculates the minimum sample size needed to detect a regression effect of a given size with adequate statistical power. It uses the anticipated R² (or the equivalent Cohen's f² effect size) and the number of predictors to determine how many observations must be collected before data collection begins.