Abstract
Many medical and epidemiologic studies incorporate an ordinal response variable. In some cases an ordinal response Y represents levels of a standard measurement scale such as severity of pain (none, mild, moderate, severe). In other cases, ordinal responses are constructed by specifying a hierarchy of separate endpoints. For example, clinicians may specify an ordering of the severity of several component events and assign patients to the worst event present from among none, heart attack, disabling stroke, and death. Still another use of ordinal response methods is the application of rank-based methods to continuous responses so as to obtain robust inferences. For example, the proportional odds model described later allows for a continuous Y and is really a generalization of the Wilcoxon-Mann-Whitney rank test.
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
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media New York
About this chapter
Cite this chapter
Harrell, F.E. (2001). Ordinal Logistic Regression. In: Regression Modeling Strategies. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3462-1_13
Download citation
DOI: https://doi.org/10.1007/978-1-4757-3462-1_13
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-2918-1
Online ISBN: 978-1-4757-3462-1
eBook Packages: Springer Book Archive