[PDF] categorical variable regression

Categorical regression quantifies categorical data by assigning numerical values to the categories, resulting in an optimal linear regression equation for the transformed variables. Categorical regression is also known by the acronym CATREG, for categorical regression.
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  • What regression do you use for categorical variables?

    Categorical variables can be included as predictors in linear regression models through the use of dummy or indicator variables.
    Interaction terms can be used to measure differences in the effect of a particular predictor between groups.

  • Which regression is best for categorical data?

    LOGISTIC REGRESSION MODEL
    This model is the most popular for binary dependent variables.
    It is highly recommended to start from this model setting before more sophisticated categorical modeling is carried out.
    Dependent variable yi can only take two possible outcomes.

  • Can categorical data be used in multiple regression?

    You definitely can, by following the same method you'd use for the first categorical predictor.
    Create dummy variables just as you would for the first such variable.

  • Can categorical data be used in multiple regression?

    A regression with categorical predictors is possible because of what's known as the General Linear Model (of which Analysis of Variance or ANOVA is also a part of).

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