看了一篇文章，作者列出了每个依变量的R2值，以及每条路径的系数和显著性，但他同时还给出了每个潜变量对它所对应的依变量的R2值。例如变量A到C的路径系数是0.294，变量B到C的路径系数是0.567，变量C的R2值是0.41.于是作者接着指出变量A可以解释变量C9%的方差，变量B可以解释变量C32%的方差，但没有说明这个结果是怎么来的。我用AMOS进行分析，没有看到关于变量与变量之间的R2值的结果，也百思不得其解作者究竟是怎么得出32%和9%的值的。请问各位高人能否指点一二。拜谢。 原文如下： Next, the path significance of each hypothesized association in the research model and variance explained (R2 value) by each path were examined. Figure 3 shows the standardized path coefficients and path significances, as reported by EQS. Intention to continue IS use was predicted by satisfaction (P = 0.57) and perceived usefulness (P = 0.29), which explained 32% and 9% of the intention variance respectively.
