What is a variable used to model the effect of categorical independent variables called?

A variable used to model the effect of categorical independent variables is called a dummy variable. These variables are created in statistical modeling when you need to include categorical data in a regression analysis. Since regression analysis typically requires numerical inputs, dummy variables convert categorical variables into a binary format (0 or 1), representing the presence or absence of a category.

For example, if you have a categorical variable representing gender with two categories (male and female), you can create a dummy variable that takes the value of 1 for males and 0 for females. This allows the model to estimate the effect that gender might have on the dependent variable while maintaining the integrity of the categorical nature of the data.

In contrast, independent variables refer more generally to inputs in a model, while dependent variables represent the outcomes being studied. Continuous variables are numerical variables that can take on a range of values, which is distinct from the binary nature of dummy variables. Consequently, the proper term for modeling the effects of categorical independent variables is indeed the dummy variable.