Azen Razia, Sass Daniel A
Department of Educational Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA.
Br J Math Stat Psychol. 2008 May;61(Pt 1):163-78. doi: 10.1348/000711006X171970. Epub 2006 Dec 28.
The performance of the asymptotic method for comparing the squared multiple correlations of non-nested models was investigated. Specifically, the increase in a given regression model's R2 when one predictor is added was compared to the increase in the same model's R2 when another predictor is added. This comparison can be used to determine predictor importance and is the basis for procedures such as Dominance Analysis. Results indicate that the asymptotic procedure provides the expected coverage rates for sample sizes of 200 or more, but in many cases much higher sample sizes are required to achieve adequate power. Guidelines and computations are provided for the determination of adequate sample sizes for hypothesis testing.
研究了用于比较非嵌套模型平方复相关系数的渐近方法的性能。具体而言，将给定回归模型在添加一个预测变量时R²的增加量与添加另一个预测变量时同一模型R²的增加量进行比较。这种比较可用于确定预测变量的重要性，并且是诸如优势分析等程序的基础。结果表明，对于样本量为200或更多的情况，渐近程序提供了预期的覆盖率，但在许多情况下，需要大得多的样本量才能获得足够的功效。提供了用于确定假设检验足够样本量的指南和计算方法。
