When using by regression, which F test is provided in the output?

[Dan Peat]

I'm running a categorical/by group regression for subsamples. When writing the results, what is the F-test that is reported (any references would also be awesome!)?

Syntax:
bys (group variable): reg (Y) (X) (controls)

I used asdoc to export it, and these are the test stats:

Mean dependent var	0.038	SD dependent var	0.981
R-squared	0.327	Number of obs	50
F-test	2.922	Prob > F	0.014
Akaike crit. (AIC)	135.128	Bayesian crit. (BIC)	150.425
*** p<.01, ** p<.05, * p<.1

I'm trying to determine if the F test is a Tukey-Kramer or a Scheffe, or is it something else?

[Andrew Musau]

The -bysort- prefix does not perform any pairwise or multiple comparisons, as far as I know. It just allows you to efficiently run the regressions for each group. I do not use asdoc from SSC, but I suspect that it may be picking up the statistics from the last estimated regression.

[Dan Peat]

Thank you. The biggest thing I am trying to figure out is if two regression coefficients in a bysort regression are statistically different. I probably should have added that to the initial ask.

[Andrew Musau]

See

h suest

[Carlo Lazzaro]

Dan:
taking shameless advantage from Andrew's helpful guidance, you may want to consider something along the following lines:

.  webuse income


.  regress inc edu exp if male

      Source |       SS           df       MS      Number of obs   =       110
-------------+----------------------------------   F(2, 107)       =     20.05
       Model |  639.919043         2  319.959521   Prob > F        =    0.0000
    Residual |  1707.31485       107  15.9562136   R-squared       =    0.2726
-------------+----------------------------------   Adj R-squared   =    0.2590
       Total |   2347.2339       109  21.5342559   Root MSE        =    3.9945

------------------------------------------------------------------------------
         inc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         edu |   1.841002    .383369     4.80   0.000     1.081018    2.600986
         exp |   1.590727   .3569439     4.46   0.000     .8831278    2.298327
       _cons |   1.783822   .3818906     4.67   0.000     1.026769    2.540876
------------------------------------------------------------------------------


.  estimates store Male


.   regress inc edu exp if !male

      Source |       SS           df       MS      Number of obs   =       167
-------------+----------------------------------   F(2, 164)       =     43.30
       Model |  1418.47853         2  709.239266   Prob > F        =    0.0000
    Residual |  2686.09306       164  16.3786162   R-squared       =    0.3456
-------------+----------------------------------   Adj R-squared   =    0.3376
       Total |  4104.57159       166  24.7263349   Root MSE        =    4.0471

------------------------------------------------------------------------------
         inc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         edu |   2.475213   .3160483     7.83   0.000     1.851165    3.099261
         exp |   1.354081   .3043211     4.45   0.000     .7531885    1.954974
       _cons |   1.250719   .3132966     3.99   0.000     .6321043    1.869334
------------------------------------------------------------------------------


.   estimates store Female


.   suest Male Female

Simultaneous results for Male, Female                      Number of obs = 277

------------------------------------------------------------------------------
             |               Robust
             | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
Male_mean    |
         edu |   1.841002   .3911029     4.71   0.000     1.074454    2.607549
         exp |   1.590727   .3320187     4.79   0.000     .9399827    2.241472
       _cons |   1.783822   .3829948     4.66   0.000     1.033166    2.534478
-------------+----------------------------------------------------------------
Male_lnvar   |
       _cons |   2.769848   .1328349    20.85   0.000     2.509497      3.0302
-------------+----------------------------------------------------------------
Female_mean  |
         edu |   2.475213   .3093986     8.00   0.000     1.868803    3.081623
         exp |   1.354081   .2982058     4.54   0.000     .7696084    1.938554
       _cons |   1.250719   .3122779     4.01   0.000      .638666    1.862773
-------------+----------------------------------------------------------------
Female_lnvar |
       _cons |   2.795977   .0976384    28.64   0.000     2.604609    2.987344
------------------------------------------------------------------------------

. test [Male_mean = Female_mean]

 ( 1)  [Male_mean]edu - [Female_mean]edu = 0
 ( 2)  [Male_mean]exp - [Female_mean]exp = 0

           chi2(  2) =    1.79
         Prob > chi2 =    0.4082
.