Wikiversity

Multiple linear regression/Multivariate outliers

< Multiple linear regression

Multivariate outliers

Check whether there are influential multivariate outlying cases using Mahalanobis distance & Cook’s D. Using PASW:

  • Linear Regression - Save - Mahalanobis and Cook's D - OK
  • SPSS will create new variables called mah_1 and coo_1.
  • Check the Residuals Statistics table in the output for the maximum Mahalanobis and Cook’s distances.
  • The maximum Mahalanobis distance should not be greater than the critical chi-square value with degrees of freedom equal to number of predictors, with critical alpha (α) =.001.
  • Cook’s D should not be greater than 1.
  • If outliers are detected, check each case, and consider removing the case from the analysis.
  • See also Francis 5.1.4.2 Screening for influential case
Retrieved from "https://en.wikiversity.org/w/index.php?title=Multiple_linear_regression/Multivariate_outliers&oldid=1026638"