So sánh phương pháp

	Phân tích lực cho Mô hình Cấu trúc Tuyến tính	Phân tích lực (Power Analysis) cho Mô hình Đa cấp và Hỗn hợp
Lĩnh vực	Thống kê	Thống kê
Họ	Hypothesis test	Hypothesis test
Năm ra đời	1996	1993
Người khởi xướng	MacCallum, Browne & Sugawara	Snijders & Bosker; Hox, Moerbeek & van de Schoot
Loại	Sample size planning (multivariate / SEM)	Sample-size planning for hierarchical designs
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.	Snijders, T.A.B. & Bosker, R.J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). SAGE. ISBN: 978-1849202015
Tên gọi khác	SEM sample size planning, covariance structure power analysis, MANOVA power analysis, SEM / Çok Değişkenli Güç Analizi	HLM power analysis, mixed-effects power analysis, clustered design power analysis, Çok Düzeyli / Karma Model Güç Analizi
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.	Multilevel power analysis is a sample-size planning procedure designed for hierarchical, clustered, or longitudinal study designs in which observations are nested within higher-level units such as students within schools or patients within clinics. Formalized in the multilevel modeling literature by Snijders and Bosker (1993, expanded 2012) and Hox, Moerbeek, and van de Schoot (2017), it accounts for the intraclass correlation (ICC) and the design effect that arises when data are clustered, ensuring that both the number of clusters and the cluster size are adequate to detect a target effect.