文章基本信息

标题：How a variable’s partial correlation with other variable(s) can make a good predictor: the suppressor variable case
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作者：Akinwande Michael Olusegun ; Aminu Muktar ; Kaile Nasiru Kabir 等
期刊名称：International Journal of Advanced Statistics and Probability
电子版ISSN：2307-9045
出版年度：2015
卷号：3
期号：2
页码：210-214
DOI：10.14419/ijasp.v3i2.5400
出版社：Journal of Advanced Computer Science & Technology
摘要：Suppression effect is one of the most elusive and difficult to understand dynamics in multiple regression analysis. Suppressor variable(s) and their dynamics in multiple regression analyses are important in reporting accurate research outcomes. However, quite a number of researchers are unfamiliar with the possible advantages and importance of these variables. Suppressor variables tend to appear useless as separate predictors, but have the potential to change the predictive ability of other variables and completely influence research outcomes. This research describes the role suppressor variables play in a multiple regression analysis and provides practical examples that further explain how suppressor effects can alter research outcomes. Finally, we employed mathematical set notation to demonstrate the concepts of suppressor effects.
关键词：Suppression Effect;Stepwise Process;Regression;Correlation;Set Notation.