急求助:路径所解释的方差(R2)值是怎么计算出来的
<br /> 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。<br /> 原文如下:<br /> 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. <br /> 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.<br /> <img src="http://397.edu.pinggu.com/attachments/month_1012/1012300532d37654fd144e2c67.gif.thumb.jpg" border="0" id="aimg_825723" onmouseover="showMenu(this.id, false, 2)" />页:
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