Question

Consider the following set of dependent and independent variables. Using technology, check for the presence of multicollinearity. If multicollinearity is present, take the necessary steps to eliminate it. у X1 12 2 9 5 13 5 14 8 22 7 26 11 25 16 34 20 24 39 37 22 X2 15 10 13 10 2 8 7 4 8 5 X3 5 15 9 12 18 17 23 20 27 30 Select the correct choice and, if necessary, fill in the answer boxes to complete your choice. (Type integers or decimals. Round to one decimal place as needed.) O A. Eliminate the variable x which has a VIF of No more variables need to be eliminated. B. Eliminate the variable x which has a VIF of Then, eliminate the variable x which has a VIF of O C. No variables need to be eliminated.

Answer 1

Sol:

use vif function from car package to get the VIF

Rcode:

y <- c(12,9,13,14,22,26,25,34,24,37)
x1 <- c(2,5,5,8,7,11,16,20,39,22)
x2 <- c(15,10,13,10,2,8,7,4,8,5)
x3 <- c(5,15,9,12,18,17,23,20,27,30)

library(car)
lmodel <- lm(y~x1+x2+x3)
vif(lmodel)

Output:

x1 x2 x3
3.801879 2.598683 6.560016

ANSWER:

OPTION (A)

eliminate the variable x3,which has a VIF of 6.6.No more variables need to be eliminated