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In 1941, Horst noticed that a variable can be totally uncorrelated with the criterion and still improve prediction by virtue of being correlated with other predictors. He christened such vari-ables suppressors, a title that implies that such variables suppress criterion-irrelevant variance in other predictors. During the 50 years that have passed since Horsts original analysis, the concept of suppression has been extended and reanalyzed. What follows provides a general approach to the analysis of suppression situations. This approach is based on coupling the analysis of 3 variate suppression situations with the applications of the concept of suppressor to the general linear model. The implications of the analysis are discussed, and some applications of the concept of suppression are provided. Suppose you are trying to predict the success of high-school students in college. \ may ask the students in high school whom they expect to succeed in college. A sociometric score for each student can then be defined and used as a predictor. It seems much less likely that you would decide to include a socio-metric variable based on the question Who is your best
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Joseph Tzelgov
Avishai Henik
Psychological Bulletin
Ben-Gurion University of the Negev
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Tzelgov et al. (Wed,) studied this question.
www.synapsesocial.com/papers/6a0278a29fad8b58aa512ce4 — DOI: https://doi.org/10.1037/0033-2909.109.3.524