文章基本信息

标题：The Goldilocks Dilemma: Impacts of Multicollinearity -- A Comparison of Simple Linear Regression, Multiple Regression, and Ordered Variable Regression Models
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作者：Baird, Grayson L ; Bieber, Stephen L.
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2016
卷号：15
期号：1
页码：18
出版社：Wayne State University
摘要：A common consideration concerning the application of multiple linear regression is the lack of independence among predictors (multicollinearity). The main purpose of this article is to introduce an alternative method of regression originally outlined by Woolf (1951), which completely eliminates the relatedness between the predictors in a multiple predictor setting.
关键词：multicollinearity; collinearity; multiple linear regression; ordered variable regression; OVR