# st: comparing anova and regression results

 From "Salisbury, Linda" <[email protected]> To "'[email protected]'" <[email protected]> Subject st: comparing anova and regression results Date Wed, 17 Jul 2002 10:16:33 -0400

```I am getting somewhat different model results from an anova procedure and it's accompanying regression output.  When regressing Y on x1 and x2, the significance levels reported for x1 and x2 are very different for anova vs. regression.  My guess is that the procedures use somewhat different algorithms.  Why are the results different and how should I interpret them?  The output follows.  Thanks in advance.
Linda Salisbury
University of Michigan
=============
. anova Y x1 x2 x1*x2

Number of obs = 99   R-squared = 0.0992
Root MSE = .688542   Adj R-squared = 0.0708

Source |  Partial SS    df       MS           F     Prob > F
---------+----------------------------------------------------
Model |  4.96141459     3  1.65380486       3.49     0.0187
|
x1 |   2.8461798     1   2.8461798       6.00     0.0161
x2 |  .302792702     1  .302792702       0.64     0.4262
x1*x2 |  1.93603708     1  1.93603708       4.08     0.0461
|
Residual |  45.0385854    95  .474090373
-----------+----------------------------------------------------
Total |       50.00    98  .510204082

. reg

Source |       SS       df       MS        Number of obs =      99
-------------+------------------------------     F(  3,    95) =    3.49
Model |  4.96141459     3  1.65380486     Prob > F      =  0.0187
Residual |  45.0385854    95  .474090373     R-squared     =  0.0992
Total |       50.00    98  .510204082     Root MSE      =  .68854
-------------------------------------------------------------------------
Y        Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------------------------------------------
_cons       2.347826    .143571    16.35   0.000     2.062802    2.632851
x1
1     .0595813   .1953754     0.30   0.761    -.3282878    .4474504
2     (dropped)
x2
6    -.3913043     .20304    -1.93   0.057    -.7943897     .011781
12    (dropped)
x1*x2
1  6       .56082   .2775219     2.02   0.046     .0098694    1.111771
1 12    (dropped)
2  6    (dropped)
2 12    (dropped)
-------------------------------------------------------------------------

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