[Stata Program]
 
use http://www.gseis.ucla.edu/courses/data/dummy

generate dum1 = (group==1)
generate dum2 = (group==2)
  
list group dum1 dum2
regress y dum1 dum2
anova y group
  
generate eff1 = (group==1)
generate eff2 = (group==2)
replace eff1=-1 if (group==3)
replace eff2=-1 if (group==3)
  
list group eff1 eff2
regress y eff1 eff2

[Stata Program]
  
use http://www.gseis.ucla.edu/courses/data/dummy
 
generate dum1 = (group==1)
generate dum2 = (group==2)
 
list group dum1 dum2
 
         group       dum1       dum2
  1.         1          1          0
  2.         1          1          0
  3.         1          1          0
  4.         1          1          0
  5.         1          1          0
  6.         2          0          1
  7.         2          0          1
  8.         2          0          1
  9.         2          0          1
 10.         2          0          1
 11.         3          0          0
 12.         3          0          0
 13.         3          0          0
 14.         3          0          0
 15.         3          0          0
 
regress y dum1 dum2
 
      Source |       SS       df       MS              Number of obs =      15
-------------+------------------------------           F(  2,    12) =   18.00
       Model |       90.00     2       45.00           Prob > F      =  0.0002
    Residual |       30.00    12        2.50           R-squared     =  0.7500
-------------+------------------------------           Adj R-squared =  0.7083
       Total |      120.00    14  8.57142857           Root MSE      =  1.5811

------------------------------------------------------------------------------
           y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        dum1 |          3          1     3.00   0.011     .8211872    5.178813
        dum2 |          6          1     6.00   0.000     3.821187    8.178813
       _cons |          3   .7071068     4.24   0.001     1.459347    4.540653
------------------------------------------------------------------------------
 
anova y group
 
                           Number of obs =      15     R-squared     =  0.7500
                           Root MSE      = 1.58114     Adj R-squared =  0.7083

                  Source |  Partial SS    df       MS           F     Prob > F
              -----------+----------------------------------------------------
                   Model |       90.00     2       45.00      18.00     0.0002
                         |
                   group |       90.00     2       45.00      18.00     0.0002
                         |
                Residual |       30.00    12        2.50   
              -----------+----------------------------------------------------
                   Total |      120.00    14  8.57142857  
 
generate eff1 = (group==1)
generate eff2 = (group==2)
replace eff1=-1 if (group==3)
replace eff2=-1 if (group==3)
 
list group eff1 eff2
  
         group       eff1       eff2
  1.         1          1          0
  2.         1          1          0
  3.         1          1          0
  4.         1          1          0
  5.         1          1          0
  6.         2          0          1
  7.         2          0          1
  8.         2          0          1
  9.         2          0          1
 10.         2          0          1
 11.         3         -1         -1
 12.         3         -1         -1
 13.         3         -1         -1
 14.         3         -1         -1
 15.         3         -1         -1
 
regress y eff1 eff2
 
      Source |       SS       df       MS              Number of obs =      15
-------------+------------------------------           F(  2,    12) =   18.00
       Model |       90.00     2       45.00           Prob > F      =  0.0002
    Residual |       30.00    12        2.50           R-squared     =  0.7500
-------------+------------------------------           Adj R-squared =  0.7083
       Total |      120.00    14  8.57142857           Root MSE      =  1.5811

------------------------------------------------------------------------------
           y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        eff1 |          0   .5773503     0.00   1.000    -1.257938    1.257938
        eff2 |          3   .5773503     5.20   0.000     1.742062    4.257938
       _cons |          6   .4082483    14.70   0.000     5.110503    6.889497
------------------------------------------------------------------------------