I used SPSS to create dummy variables for three different shops. Shop 1 was coded 0, shop 2 was coded 1 and shop 3 was coded 2. In my output I see that the slope coefficients (B) for shop 2 and 3 are almost identical, with almost identical CI, t statistics and p values. What does that mean, and is it necessary to separate the dummy variables when slope coefficient are so similar? And what could I have done instead if not separate them in dummies?

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    $\begingroup$ You should only have two dummy variables for the three shops. $\endgroup$
    – gueststata
    May 22, 2014 at 14:52

1 Answer 1


Ideally you should dummy code it as two variables. Then the third variable gets accounted for by the intercept of the model. Assuming these two variables are the only variables in the model,the coefficients you obtain are the difference between each shop with the non-dummy-coded shop along with the overall average. So its the incremental value when one goes from shop3 to shop 1 or shop3 to shop2 (assuming you didnt dummy code shop3)

You might want to look into contrasts coding to know more about using dummy variables in a regression model http://en.wikipedia.org/wiki/Contrast_(statistics) . Do check the external links provided in the wiki page that provides a really good explantion on contrasts.


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