Difference between revisions of "Multiple Regression Analysis"
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== Collinearity and Multicollinearity == | == Collinearity and Multicollinearity == | ||
| − | Collinearity is "a condition that exists when two predictors correlate very strongly" (Meyers, Gamst, & Guarino, 2017, p. 189). | + | '''Collinearity''' is "a condition that exists when two predictors correlate very strongly" (Meyers, Gamst, & Guarino, 2017, p. 189). |
| − | Multicollinearity is a condition that exists when "more than two predictors correlate very strongly" (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: | ||
| + | |||
| + | 1. Click "Analyze" | ||
| + | |||
| + | 2. Then Select "Regression" | ||
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| + | 3. Click "Linear" | ||
| + | |||
| + | 4. Put all the IV's in the IV section and then move ONE IV into the DV box. | ||
| + | |||
| + | 5. Uncheck all boxes in "Statistics" except for "Collinearity Diagnostics" | ||
| + | |||
| + | 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. | ||
| + | |||
| + | Detecting Multicollinearity in SPSS [https://www.youtube.com/watch?v=oPXjQCtyoG0] | ||
''Contribution by: Britany Kuslis, WCSU Cohort 8'' | ''Contribution by: Britany Kuslis, WCSU Cohort 8'' | ||
| − | + | ||
| + | References: | ||
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| + | Gaskin, James, director. Detecting Multicollinearity in SPSS. YouTube, YouTube, 26 Mar. 2011, www.youtube.com/watch?v=oPXjQCtyoG0. | ||
| + | |||
Meyers, S., Gamst, G., & Guarino, A.J. (2017). ''Applied multivariate research: Design and interpretation.'' Thousand Oaks, CA: Sage Publications. | Meyers, S., Gamst, G., & Guarino, A.J. (2017). ''Applied multivariate research: Design and interpretation.'' Thousand Oaks, CA: Sage Publications. | ||
Revision as of 19:20, 16 November 2019
Collinearity and Multicollinearity
Collinearity is "a condition that exists when two predictors correlate very strongly" (Meyers, Gamst, & Guarino, 2017, p. 189).
Multicollinearity is a condition that exists when "more than two predictors correlate very strongly" (p. 189).
Steps for How to Detect Multicollinearity in SPSS:
1. Click "Analyze"
2. Then Select "Regression"
3. Click "Linear"
4. Put all the IV's in the IV section and then move ONE IV into the DV box.
5. Uncheck all boxes in "Statistics" except for "Collinearity Diagnostics"
6. Click "Ok"
- 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.
Detecting Multicollinearity in SPSS [1]
Contribution by: Britany Kuslis, WCSU Cohort 8
References:
Gaskin, James, director. Detecting Multicollinearity in SPSS. YouTube, YouTube, 26 Mar. 2011, www.youtube.com/watch?v=oPXjQCtyoG0.
Meyers, S., Gamst, G., & Guarino, A.J. (2017). Applied multivariate research: Design and interpretation. Thousand Oaks, CA: Sage Publications.
