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首页> 外文期刊>The British journal of mathematical and statistical psychology >Comparing the squared multiple correlation coefficients of non-nested models: An examination of confidence intervals and hypothesis testing
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Comparing the squared multiple correlation coefficients of non-nested models: An examination of confidence intervals and hypothesis testing

机译：比较非嵌套模型的平方多重相关系数：置信区间和假设检验

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摘要

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 R-2 when one predictor is added was compared to the increase in the same model's R-2 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.
机译：研究了渐近方法用于比较非嵌套模型平方相关的平方的性能。具体而言，将添加一个预测变量时给定回归模型的R-2的增加与添加另一个预测变量时相同模型的R-2的增加进行比较。此比较可用于确定预测变量的重要性，并且是诸如“优势分析”之类的过程的基础。结果表明，渐近过程可为200个或更多的样本量提供预期的覆盖率，但在许多情况下，需要更高的样本量才能获得足够的功效。提供了指南和计算方法，用于确定假设检验的适当样本量。

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