There are many different types of regression analysis. Some of the most common types are included in this guide: linear, logistic, ordinal, multinomial, Poisson, and Cox regression. Which one you should choose depends on your outcome (y).

Continuous	Linear regression
Nominal with two categories, i.e. binary	Logistic regression
Nominal with more than two categories, i.e. non-binary	Multinomial regression
Ordinal	Ordinal regression
Count	Poisson regression
Time-to-event	Cox regression

However, your x-variable(s) can take on any form – they can be categorical or continuous. If you include only one x-variable in your regression analysis, this is called simple (or bivariate) regression analysis. If you include two or more x-variables in your regression analysis, this is called multiple regression analysis. In multiple regression analysis, it is possible to mix different types of x-variables: you can thus use both categorical and continuous x-variables.