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Regression Commonality Analysis: A Technique for Quantitative Theory Building

机译:回归共性分析:定量理论构建技术

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When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality analysis to more completely interpret their regression effects and thereby inform theory. Using an empirical example from published literature, readers will see how regression commonality analysis can uncover important theoretical relationships that might be left undetected by only examining beta weights.
机译:当涉及多元线性回归分析(MLR)时,社会和行为科学研究者通常在评估预测变量对回归模型的贡献时主要依赖beta权重。提出一种未充分利用的统计技术,本文介绍组织研究人员如何使用共性分析来更完整地解释其回归效应,从而为理论提供依据。使用已发表文献中的经验示例,读者将看到回归共性分析如何发现仅通过检查β权重可能无法发现的重要理论关系。

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