Methodology review: Estimation of population validity and cross-validity, and the use of equal weights in prediction
Methodology review: Estimation of population validity and cross-validity, and the use of equal weights in prediction
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DOI：
10.1177/01466216970214001
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发表时间：
1997-12-01
影响因子：
1.2
通讯作者：
Fleer, PF
中科院分区：
文献类型：
--
作者：
Raju, NS;Bilgic, R;Fleer, PF
在多元回归中，使用普通最小二乘（OLS）程序获得最佳线性权重。然而，这些线性加权组合的预测可能无法最佳地预测相同的标准，从人口中的样本（人口有效性）或其他样本从同一人口（人口交叉有效性）。为了更准确地估计总体效度和总体交叉效度，一些研究者和从业者使用公式或传统的经验方法来获得估计值。其他人则建议使用等权重程序，作为基于公式和经验的程序的替代办法。本综述发现，基于公式的程序可以用来代替经验验证估计人口效度或代替经验交叉验证估计人口交叉效度。当观测到的多重相关性为低至中等，且预测因子-标准相关性之间的变异性较低时，等权重程序是一种可行的替代方法。尽管有这些调查结果，但很难推荐一种基于公式的估计数优于另一种，因为没有一项研究包括所有现有公式。并对今后的研究和应用提出了建议。
In multiple regression, optimal linear weights are obtained using an ordinary least squares (OLS) procedure. However, these linear weighted combinations of predictors may not optimally predict the same criterion in the population from which the sample was drawn (population validity) or other samples drawn from the same population (population cross-validity). To achieve more accurate estimates of population validity and population cross-validity, some researchers and practitioners use formulas or traditional empirical methods to obtain the estimates. Others have suggested using the equal weights procedure as an alternative to the formula-based and empirical procedures. This review found that formula-based procedures can be used in place of empirical validation for estimating population validity or in place of empirical cross-validation for estimating population cross-validity. The equal weights procedure is a viable alternative when the observed multiple correlation is low to moderate and the variability among predictor-criterion correlations is low. Despite these findings, it is difficult to recommend one formula-based estimate over another because no single study has included all of the currently available formulas. Suggestions are offered for future research and application of these techniques.