Pairwise Regression Weight Contrasts: Models for Allocating Psychological Resources

IF 1.9 3区心理学 Q2 EDUCATION & EDUCATIONAL RESEARCH

Journal of Educational and Behavioral Statistics Pub Date : 2023-10-13 DOI:10.3102/10769986231200155

Mark L. Davison, Hao Jia, Ernest C. Davenport

引用次数: 0

Abstract

Researchers examine contrasts between analysis of variance (ANOVA) effects but seldom contrasts between regression coefficients even though such coefficients are an ANOVA generalization. Regression weight contrasts can be analyzed by reparameterizing the linear model. Two pairwise contrast models are developed for the study of qualitative differences among predictors. One leads to tests of null hypotheses that the regression weight for a reference predictor equals each of the other weights. The second involves ordered predictors and null hypotheses that the weight for a predictor equals that for the variables just above or below in the ordering. As illustration, qualitative differences in high school math course content are related to math achievement. The models facilitate the study of qualitative differences among predictors and the allocation of resources. They also readily generalize to moderated, hierarchical, and generalized linear forms.

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两两回归权重对比:心理资源分配模型

研究人员检查了方差分析(ANOVA)效应之间的对比，但很少检查回归系数之间的对比，即使这些系数是方差分析的泛化。回归权重对比可以通过重新参数化线性模型来分析。为研究预测因子之间的质性差异，开发了两个两两对比模型。其中一个导致零假设的检验，即参考预测器的回归权重等于其他权重。第二种涉及有序预测器和零假设，即预测器的权重等于排序中上下变量的权重。例如，高中数学课程内容的质性差异与数学成绩有关。这些模型有助于研究预测者之间的质的差异和资源的分配。它们也很容易推广到适度的、分层的和广义的线性形式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Educational and Behavioral Statistics Multiple-

CiteScore

4.40

自引率

4.20%

发文量

期刊介绍： Journal of Educational and Behavioral Statistics, sponsored jointly by the American Educational Research Association and the American Statistical Association, publishes articles that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also of interest. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority. The Journal of Educational and Behavioral Statistics provides an outlet for papers that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis, provide properties of these methods, and an example of use in education or behavioral research. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also sometimes accepted. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority.