Hi forum!
I have a question for you. I tried to assess the linearity assumption of my multiple linear regression model by testing the "structure" of the standardized residuals against the values of my predictors; but I'm not so sure this is the best way to do that. I attached an example of what I've done.
Code:
. regress consumilog disoccup inattivitàlog dem_impreselog retrib_medialog componenti_f
> amsqr

      Source |       SS       df       MS              Number of obs =     107
-------------+------------------------------           F(  5,   101) =  161.28
       Model |  5.44754193     5  1.08950839           Prob > F      =  0.0000
    Residual |  .682297905   101  .006755425           R-squared     =  0.8887
-------------+------------------------------           Adj R-squared =  0.8832
       Total |  6.12983984   106  .057828678           Root MSE      =  .08219

-----------------------------------------------------------------------------------
       consumilog |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
         disoccup |  -.0139411   .0028199    -4.94   0.000     -.019535   -.0083473
    inattivitàlog |  -.6843887   .0814612    -8.40   0.000    -.8459859   -.5227915
   dem_impreselog |    .015953   .0126544     1.26   0.210      -.00915     .041056
  retrib_medialog |   .3489728   .1838609     1.90   0.061    -.0157578    .7137034
componenti_famsqr |   .0385899   .0133636     2.89   0.005     .0120802    .0650997
            _cons |   6.341054   1.937408     3.27   0.001     2.497758    10.18435
-----------------------------------------------------------------------------------
Code:
predict consumires, rstandard
Code:
 scatter consumires disoccup