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st: Incomplete results of linear regression with interaction variable
From
Jean-Baptiste Peraldi <[email protected]>
To
[email protected]
Subject
st: Incomplete results of linear regression with interaction variable
Date
Wed, 20 Mar 2013 22:56:04 +0100
Hi Statalisters,
I want to to run two linear regressions with dichotomous independant variables, where one contains an interaction variable.
It appears that the regression with the interaction variable gives only results for the coefficients.
Here is the content of my database:
***
. list
+---------------------------------------------------------------------------+
| race quality mean_call sd_call n r_q |
|----------------------------------------------------------------------------|
1. | 0 0 .0854185 .279624 1159 0 |
2. | 0 1 .1069024 .3091192 1188 0 |
3. | 1 0 .0569456 .2318388 1159 0 |
4. | 1 1 .0675791 .2511297 1169 1 |
+---------------------------------------------------------------------------+
***
The first regression is :
" mean_call = cst + beta1*race "
where "race" is a dichotomous (0 or 1) variable.
The second regression contains an interaction variable :
" mean_call = cst + beta1*race + beta2*quality + beta3*race*quality " where both "race" and "quality" are dichotomous (0 or 1) variables.
When running the first regression, I get full results:
***
. reg mean_call race
Source | SS df MS Number of obs = 4
-------------+----------------------------------------- F( 1, 2) = 8.00
Model | .001149076 1 .001149076 Prob > F = 0.1056
Residual | .000287314 2 .000143657 R-squared = 0.8000
-------------+----------------------------------------- Adj R-squared = 0.7000
Total | .00143639 3 .000478797 Root MSE = .01199
------------------------------------------------------------------------------
mean_call | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
race | -.033898 .0119857 -2.83 0.106 -.0854683 .0176723
_cons | .0961604 .0084752 11.35 0.008 .0596947 .1326261
------------------------------------------------------------------------------
***
For the second regression, I create the interaction variable and run the regression
***
. gen r_q = race*quality
. reg mean_call race quality r_q
Source | SS df MS Number of obs = 4
-------------+---------------------------------------- F( 3, 0) = .
Model | .00143639 3 .000478797 Prob > F = .
Residual | 0 0 . R-squared = 1.0000
-------------+---------------------------------------- Adj R-squared = .
Total | .00143639 3 .000478797 Root MSE = 0
------------------------------------------------------------------------------
mean_call | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
race | -.0284728 . . . . .
quality | .0214839 . . . . .
r_q | -.0108504 . . . . .
_cons | .0854185 . . . . .
------------------------------------------------------------------------------
***
Here we can see that we get results for the coefficients only, which is quite weird. I will be glad if you can help me solve this problem.
Thanks for your consideration.
Jean-Baptiste P.
***
Stata/IC 12.1 for Mac (64-bit Intel)
Revision 25 Feb 2013
***
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