So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Phân tích đường dẫn mạnh mẽ× | Phân tích nhân tố xác nhận mạnh mẽ× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ | Latent structure | Latent structure |
| Năm ra đời≠ | 1998 | 1984–1994 |
| Người khởi xướng≠ | Yuan & Bentler (robust SEM/path framework); Huber (M-estimation foundation) | Satorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator) |
| Loại≠ | Causal path modeling with robust estimation | Confirmatory latent variable model with robust estimation |
| Công trình gốc≠ | Yuan, K.-H. & Bentler, P. M. (1998). Robust mean and covariance structure analysis. British Journal of Mathematical and Statistical Psychology, 51(1), 63–88. DOI ↗ | Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link ↗ |
| Tên gọi khác | robust PA, path analysis with robust standard errors, robust causal path modeling, robust structural path modeling | Robust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFA |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | Robust path analysis applies robust estimation — such as sandwich standard errors or M-estimation — to path models that specify directed causal relationships among observed variables. It preserves valid inference about path coefficients and indirect effects when data violate normality, contain outliers, or exhibit heteroscedasticity that would distort conventional standard errors. | Robust confirmatory factor analysis fits a pre-specified factor structure to observed data while correcting standard errors and goodness-of-fit statistics for violations of multivariate normality. It is the preferred variant of CFA whenever Likert-type, skewed, or kurtotic indicators make the classical normal-theory estimator unreliable. |
| ScholarGateBộ dữ liệu ↗ |
|
|