Assessing proportionality in the proportional odds model for ordinal logistic regression.

Brant, Rollin

doi:10.2307/2532457

Cited by 1,864Statistical Methods and ApplicationsStatistical Methods in EpidemiologyStatistical Methods and Bayesian Inference

Assessing proportionality in the proportional odds model for ordinal logistic regression.

Brant, Rollin·1990·Biometrics

DOI 10.2307/2532457

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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.

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The proportional odds assumption of logistic regression is not violated (Brant test P = 0.59).
“The proportional odds assumption of logistic regression is not violated (using a Brant test [26], P = 0.59).”
From Extending body space in immersive virtual reality: a very long arm illusion (2012) · cites this paper as [26]

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Authors: Brant, R.
Affiliations: University of Calgary (CA)
Corresponding author: Brant, Rollin
ORCID: Brant, Rollin
Venue: Biometrics
Publisher: JSTOR
Published: 1990-12
Volume: 46
Issue: 4
Pages: 1171
ISSN: 0006-341X (ISSN-L)
DOI: 10.2307/2532457
OpenAlex: W2016013569
Cited by: 1,864
References: 5
Citations by year: 2026: 213 · 2025: 135 · 2024: 135 · 2023: 161 · 2022: 168 · 2021: 145 · 2020: 141 · 2019: 99 · 2018: 76 · 2017: 69 · 2016: 68 · 2015: 57 · 2014: 64 · 2013: 51 · 2012: 45
FWCI: 0.94
Type: journal article
Language: en
Open access: closed
Locations: Biometrics (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: proportional odds model, ordinal logistic regression, proportional odds assumption, goodness-of-fit tests, binary logistic regression, asymptotic distribution, bootstrap simulation, correlated binary responses
MeSH terms: Biometry, Humans, Regression Analysis, Tissue Donors, Models, Statistical, Liver Transplantation

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Assessing proportionality in the proportional odds model for ordinal logistic regression.

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