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  3. HR Analytics: Predicting Employee Churn in R

Exercise

Dealing with multicollinearity

In the previous exercise, you found that multicollinearity exists in your model by reviewing the VIF values of independent variables. Follow the steps below to remove multicollinearity:

  • Step 1: Calculate VIF of the model
  • Step 2: Identify if any variable has VIF greater than or equal to 5
    • Step 2a: Remove the variable from the model if it has a VIF greater than or equal to 5
    • Step 2b: If there are multiple variables with VIF greater than 5, only remove the variable with the highest VIF
  • Step 3: Repeat steps 1 and 2 until VIF of all variables is less than 5

Instructions 1/2

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  • As identified in the previous exercise, level has the highest VIF, so remove this variable from your model.
  • Check for multicollinearity in this new model.
  • Which variable has the highest VIF? Assign the variable name as a string to highest.