Abstract
In this chapter, the standard logistic model is extended to handle outcome variables that have more than two categories. Polytomous logistic regression is used when the categories of the outcome variable are nominal, that is, they do not have any natural order. When the categories of the outcome variable do have a natural order, ordinal logistic regression may also be appropriate.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Kleinbaum, D.G., Klein, M. (2010). Polytomous Logistic Regression. In: Logistic Regression. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1742-3_12
Download citation
DOI: https://doi.org/10.1007/978-1-4419-1742-3_12
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1741-6
Online ISBN: 978-1-4419-1742-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)