From Practical Statistics for Educators
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| − | == Collinearity and Multicollinearity ==
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| − | '''Collinearity''' is "a condition that exists when two predictors correlate very strongly" (Meyers, Gamst, & Guarino, 2017, p. 189).
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| − | '''Multicollinearity''' is a condition that exists when "more than two predictors correlate very strongly" (p. 189).
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| − | Steps for How to Detect Multicollinearity in SPSS:
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| − | 1. Click "Analyze"
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| − | 2. Then Select "Regression"
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| − | 3. Click "Linear"
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| − | 4. Put all the IV's in the IV section and then move ONE IV into the DV box.
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| − | 5. Uncheck all boxes in "Statistics" except for "Collinearity Diagnostics"
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| − | 6. Click "Ok"
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| − | *The output should indicate if there is a VIF. If the VIF is above 3 there is likely multicollinearity issues, and if it is above 10 you are highly likely to have multicollinearity issues.
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| − | Detecting Multicollinearity in SPSS [https://www.youtube.com/watch?v=oPXjQCtyoG0]
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| − | ''Contribution by: Britany Kuslis, WCSU Cohort 8''
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| − | References:
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| − | Gaskin, James, director. ''Detecting Multicollinearity in SPSS''. YouTube, YouTube.com, 26 Mar. 2011, www.youtube.com/watch?v=oPXjQCtyoG0.
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| − | Meyers, S., Gamst, G., & Guarino, A.J. (2017). ''Applied multivariate research: Design and interpretation.'' Thousand Oaks, CA: Sage Publications.
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Latest revision as of 08:03, 2 December 2019
