Dummy Variable Trap with Example Using R and Excel
If there is an intercept in the regression model, the number of dummy variables must be one less than the number of classifications of each qualitative variable.
If you drop the (common) intercept from the model, you can have as many dummy variables as the number of categories of the dummy variable.
The coefficient of a dummy variable must always be interpreted in relation to the reference category.
Dummy variables can interact with quantitative regressors as well as with qualitative regressors. If a model has several qualitative variables with several categories, introduction of dummies for all the combinations can consume a large number of degrees of freedom.
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