How to test for goodness of fit in ordinal logistic regression models
Morten W. Fagerland
Oslo Centre for Biostatistics and Epidemiology
Research Support Services
Oslo University Hospital
Oslo, Norway
[email protected]
|
David W. Hosmer
Department of Mathematics and Statistics
University of Vermont
Burlington, VT
|
Abstract. Ordinal regression models are used to describe the relationship between an
ordered categorical response variable and one or more explanatory variables.
Several ordinal logistic models are available in Stata, such as the
proportional odds, adjacent-category, and constrained continuation-ratio
models. In this article, we present a command (ologitgof) that
calculates four goodness-of-fit tests for assessing the overall adequacy of
these models. These tests include an ordinal version of the
Hosmer–Lemeshow test, the Pulkstenis–Robinson chi-squared and
deviance tests, and the Lipsitz likelihood-ratio test. Together, these tests
can detect several different types of lack of fit, including wrongly specified
continuous terms, omission of different types of interaction terms, and an
unordered response variable.
View all articles by these authors:
Morten W. Fagerland, David W. Hosmer
View all articles with these keywords:
ologitgof, Hosmer–Lemeshow test, Pulkstenis–Robinson chi-squared and deviance tests, Lipsitz likelihood-ratio test, ordinal models, proportional odds, adjacent category, continuation ratio
Download citation: BibTeX RIS
Download citation and abstract: BibTeX RIS
|
