CODEWITHSUNDEEP
commandregressionstata
Giulia Maria Wagner
Giulia Maria Wagner

Reputation: 27

how to use estat vif in the right way

I have 2 questions concerning estat vif to test multicollinearity:

  1. Is it correct that you can only calculate estat vif after the regress command?
  2. If I execute this command Stata only gives me the vif of one independent variable.
    • How do I get the vif of all the independent variables?

Upvotes: 1

Views: 2111

Answers (1)

Nick Cox
Nick Cox

Reputation: 37208

Q1. I find estat vif documented under regress postestimation. If you can find it documented under any other postestimation heading, then it is applicable after that command.

Q2. You don't give any examples, reproducible or otherwise, of your problem. But estat vif by default gives a result for each predictor (independent variable). 

. sysuse auto, clear
(1978 Automobile Data)

. regress mpg weight price

      Source |       SS           df       MS      Number of obs   =        74
-------------+----------------------------------   F(2, 71)        =     66.85
       Model |  1595.93249         2  797.966246   Prob > F        =    0.0000
    Residual |  847.526967        71  11.9369995   R-squared       =    0.6531
-------------+----------------------------------   Adj R-squared   =    0.6434
       Total |  2443.45946        73  33.4720474   Root MSE        =     3.455

------------------------------------------------------------------------------
         mpg |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      weight |  -.0058175   .0006175    -9.42   0.000    -.0070489   -.0045862
       price |  -.0000935   .0001627    -0.57   0.567     -.000418    .0002309
       _cons |   39.43966   1.621563    24.32   0.000     36.20635    42.67296
------------------------------------------------------------------------------

. estat vif

    Variable |       VIF       1/VIF  
-------------+----------------------
       price |      1.41    0.709898
      weight |      1.41    0.709898
-------------+----------------------
    Mean VIF |      1.41

Upvotes: 1

Related Questions