# [Knowledge Sharing] 关于 Variance explained解释力 R square (R 2)的

[Knowledge Sharing] 关于 Variance explained解释力 R square (R 2)的要求？

20230407 萧文龙敬上

1. 重要的 内生潜在变量的Variance explained解释力 R square (R 2)太低，

2. 重要的 内生潜在变量的Variance explained解释力 来自于 调节变量或控制调节变量

Note 1 : 二手数据和 行为的数据在某些子领域 (例如 经济的子领域) 是不看 R square， 而是注重在路径系数是否有显著影响。

Note 2： 一般对于人的问卷调查（Survey）是需要严格要求 R square解释力大小，否则对于现象而言，毫无解释能力。

In general, the value of R 2 is considered as follows: 0.19 (weak), 0.33 (moderate), and 0.67 (substantial) (Chin, 1998; Henseler et al., 2009). In practice, a typical marketing research study has a significance level of 5%, a statistical power of 80%, and R square values of at least 0.25 (Wong, 2013).

Chin, W.W. (1998), “The partial least squares approach to structural equation modeling”, in Marcoulides, G.A. (Ed.), Modern Methods for Business Research (pp. 295-358.), Erlbaum, Mahwah, NJ,

Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(2009), 277–320

Ken Kwong-Kay Wong (2013) Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS, Marketing Bulletin, 2013, 24, Technical Note 1 （被引用 3435） 次

https://blog.sciencenet.cn/blog-3444471-1383312.html

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