Assessing Proportionality in the Proportional Odds Model for Ordinal Logistic Regression

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ID: 291791
1990
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Abstract
The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered categories. The model may be represented by a series of logistic regressions for dependent binary variables, with common regression parameters reflecting the proportional odds assumption. Key to the valid application of the model is the assessment of the proportionality assumption. An approach is described arising from comparisons of the separate (correlated) fits to the binary logistic models underlying the overall model. Based on asymptotic distributional results, formal goodness-of-fit measures are constructed to supplement informal comparisons of the different fits. A number of proposals, including application of bootstrap simulation, are discussed and illustrated with a data example.
Reference Key
openalex_W2016013569 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Rollin Brant
Journal biometrics
Year 1990
DOI
10.2307/2532457
URL
https://doi.org/10.2307/2532457
Keywords Keywords not found

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