Latent structureLatent Variable Modeling

偏最小二乘结构方程模型

偏最小二乘结构方程模型（PLS-SEM）是一种基于方差的结构方程模型方法，由Herman Wold（1985）开发，通过最大化因变量的解释方差来估计潜变量模型。与协方差为基础的SEM不同，PLS-SEM尤其适用于探索性研究、中小样本、具有多个潜在变量的复杂模型以及非正态数据。

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The neighbourhood of related methods — select a node to explore.

偏最小二乘结构方程模型

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Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445
Wold, H. (1985). Partial least squares. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of Statistical Sciences (Vol. 6, pp. 581-591). Wiley. ISBN: 9780471822622
Chin, W. W. (2010). How to write up and report PLS analyses. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (pp. 655-690). Springer. DOI: 10.1007/978-3-540-32827-8_29 ↗

ScholarGate. (2026, June 3). Partial Least Squares Structural Equation Modeling. ScholarGate. https://scholargate.app/zh/psychometrics/pls-sem

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.