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# Re-Post: Stata 11 - Factor variables in a regression command

 From Ricardo Basurto To statalist@hsphsun2.harvard.edu Subject Re-Post: Stata 11 - Factor variables in a regression command Date Sat, 1 May 2010 01:38:52 -0400

```I apologize for the re-posting.  My original message was split in two
and parts of it were cut out. I hope submitting directly from within
Gmail will solve the problem. Original message below:

============================================================

I am having trouble understanding the difference between a regression that
uses a cross operator (#) and one that uses a cross factorial operator (##).
For example, this is the output I get from running two different
regressions:

. logistic y a#b

Logistic regression                             Number of obs   =      19670
LR chi2(3)      =       7.71
Prob > chi2     =     0.0525
Log likelihood = -1473.1898                     Pseudo R2       =     0.0026

----------------------------------------------------------------------------
y | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Int.]
-----------+----------------------------------------------------------------
a#b |
0 1  |   1.567419   .2804138     2.51   0.012     1.1038    2.2256
1 0  |   1.447424   .2588797     2.07   0.039     1.0194    2.0551
1 1  |   1.211988   .2246236     1.04   0.300     .84283    1.7428
----------------------------------------------------------------------------

. logistic y a##b

Logistic regression                             Number of obs   =      19670
LR chi2(3)      =       7.71
Prob > chi2     =     0.0525
Log likelihood = -1473.1898                     Pseudo R2       =     0.0026

----------------------------------------------------------------------------
y | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Int.]
-----------+----------------------------------------------------------------
1.a |   1.447424   .2588797     2.07   0.039     1.0194    2.0551
1.b |   1.567419   .2804138     2.51   0.012     1.1038    2.2256
|
a#b |
1 1  |   .5342167   .1302597    -2.57   0.010     .33125    .86152
----------------------------------------------------------------------------

```