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# st: testing the equivalance of the coefficient of the same variable in two (nested) models

 From Evelyn Ersanilli To "statalist@hsphsun2.harvard.edu" Subject st: testing the equivalance of the coefficient of the same variable in two (nested) models Date Sat, 14 Aug 2010 23:20:05 +0100

```Dear statalisters,

I want to test whether the estimated coefficient of a variable (a dummy variable, let's call it X) is the same in two models.
In the second model I add three additional variables, and I want to know whether the observed decrease in size of the estimated coefficient of X is significant.
X has a significant effect in both models, but in the second model the estimated coefficient is smaller than in the first model.

Based on a search through the statalist archives I wrote the following command lines;

**************************
local controls "(varlist)"
reg hcident `controls' if genb>1 & nomiss2==1
est sto hc1
reg hcident `controls' seet seehc dscrfrq if genb>1 & nomiss2==1
est sto hc0
suest hc0 hc1
test [hc0_mean]X=[hc1_mean]X
****************************
(In case you are wondering: X is significant in both models at p<.001. I used markout to run both models on the same sample)

I have two questions
1. What does the '_mean' mean? Is it the mean of the size of the estimation of X or the mean of something else? If I leave it out or replace it by '_b' or 'coef' I get an error message.

2. The test is significant (Prob > chi2 =    0.0001), so the H0 [hc0_mean]X=[hc1_mean]X is refuted. I interpret this as meaning that the three variables I add in the second model (seet seehc dscrfrq) in part account for the effect of X. Is this a correct interpretation?

Many thanks

Kind regards,

Evelyn

Evelyn Ersanilli
Research Officer EUMAGINE project
International  Migration Institute (IMI)
University of Oxford
Tel: +44 (0) 1865 271925

www.eumagine.org

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