Extracting the Variance In flation Factor and Other Multicollinearity Diagnostics from Typical Regression Results

Multicollinearity is a potential problem in all regression analyses. However, the examination of multicollinearity is rarely reported in primary studies. In this article we discuss and show several post hoc methods for assessing multicollinearity. One such multicollinearity diagnostic is the varianc...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Basic and applied social psychology Jg. 39; H. 2; S. 81
Hauptverfasser: Thompson, Christopher Glen, Kim, Rae Seon, Aloe, Ariel M, Becker, Betsy Jane
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Mahwah Psychology Press 04.03.2017
Schlagworte:
Correlation analysis
Inflation
Regression analysis
ISSN:0197-3533, 1532-4834
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Multicollinearity is a potential problem in all regression analyses. However, the examination of multicollinearity is rarely reported in primary studies. In this article we discuss and show several post hoc methods for assessing multicollinearity. One such multicollinearity diagnostic is the variance inflation factor. We outline the post hoc variance inflation factor method, which computes the variance inflation factor from the standardized regression coefficient and semi-partial correlation, both of which can be calculated from commonly reported regression results. Three examples of computing multicollinearity diagnostics using data from published studies are shown. We conclude with a discussion and practical implications.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0197-3533
1532-4834
DOI:10.1080/01973533.2016.1277529