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Re: st: Incomplete results of linear regression with interaction variable


From   William Buchanan <william@williambuchanan.net>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Incomplete results of linear regression with interaction variable
Date   Wed, 20 Mar 2013 15:14:16 -0700

Hi Jean-Baptiste,

Look at your F statistic.  You don't have enough observations to estimate that model.

HTH,
Billy


On Mar 20, 2013, at 2:56 PM, Jean-Baptiste Peraldi <jean-baptiste.peraldi@unil.ch> wrote:

> 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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