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ERIC Number: ED599869
Record Type: Non-Journal
Publication Date: 2017-Apr-28
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-
EISSN: N/A
Available Date: N/A
The Effect of Multicollinearity on Prediction in Regression Models
Mundfrom, Daniel J.; DePoy Smith, Michelle L.; Kay, Lisa W.
AERA Online Paper Repository, Paper presented at the Annual Meeting of the American Educational Research Association (San Antonio, TX, Apr 27-May 1, 2017)
It is widely known that the presence of multicollinearity in a dataset can have detrimental effects on determining which predictors are responsible for the variation in the response (e.g. Pedhazur, 1982). There also exist some indication that the presence of multicollinearity does not impact one's ability to accurately estimate/predict the value of the response variable for any specific values of the predictors (e.g. Weiss, 2012). This idea is not widely present in regression textbooks, nor is there much research literature that supports it. This study was conducted to examine this relationship in situations that varied in the number of predictors, strength of the association between the predictors and the response, sample size, and level of the multicollinearity among the predictors.
AERA Online Paper Repository. Available from: American Educational Research Association. 1430 K Street NW Suite 1200, Washington, DC 20005. Tel: 202-238-3200; Fax: 202-238-3250; e-mail: subscriptions@aera.net; Web site: http://www.aera.net
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A