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Ordinal Logistic Regression in Medical Research
Medical research workers are making increasing use of logistic regression analysis for binary and ordinal data. The purpose of this paper is to give a non-technical introduction to logistic regression models for ordinal response variables. We address issues such as the global concept and interpetati...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royal College of Physicians of London
1997
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420958/ https://www.ncbi.nlm.nih.gov/pubmed/9429194 |
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author | Bender, Ralf Grouven, Ulrich |
author_facet | Bender, Ralf Grouven, Ulrich |
author_sort | Bender, Ralf |
collection | PubMed |
description | Medical research workers are making increasing use of logistic regression analysis for binary and ordinal data. The purpose of this paper is to give a non-technical introduction to logistic regression models for ordinal response variables. We address issues such as the global concept and interpetation of logistic models, the model building procedure from a practical point of view, and the assessment of the model adequacy. For illustrative purposes we apply these methods to real data of a study investigating the association between glycosylated haemoglobin and retinopathy. We give some recommendations for the use and assessment of ordinal logistic regression models in medical research. |
format | Online Article Text |
id | pubmed-5420958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 1997 |
publisher | Royal College of Physicians of London |
record_format | MEDLINE/PubMed |
spelling | pubmed-54209582019-01-22 Ordinal Logistic Regression in Medical Research Bender, Ralf Grouven, Ulrich J R Coll Physicians Lond Education and Training Medical research workers are making increasing use of logistic regression analysis for binary and ordinal data. The purpose of this paper is to give a non-technical introduction to logistic regression models for ordinal response variables. We address issues such as the global concept and interpetation of logistic models, the model building procedure from a practical point of view, and the assessment of the model adequacy. For illustrative purposes we apply these methods to real data of a study investigating the association between glycosylated haemoglobin and retinopathy. We give some recommendations for the use and assessment of ordinal logistic regression models in medical research. Royal College of Physicians of London 1997 /pmc/articles/PMC5420958/ /pubmed/9429194 Text en © Journal of the Royal College of Physicians of London 1997 http://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) , which permits non-commercial use and redistribution provided that the original author and source are credited. |
spellingShingle | Education and Training Bender, Ralf Grouven, Ulrich Ordinal Logistic Regression in Medical Research |
title | Ordinal Logistic Regression in Medical Research |
title_full | Ordinal Logistic Regression in Medical Research |
title_fullStr | Ordinal Logistic Regression in Medical Research |
title_full_unstemmed | Ordinal Logistic Regression in Medical Research |
title_short | Ordinal Logistic Regression in Medical Research |
title_sort | ordinal logistic regression in medical research |
topic | Education and Training |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420958/ https://www.ncbi.nlm.nih.gov/pubmed/9429194 |
work_keys_str_mv | AT benderralf ordinallogisticregressioninmedicalresearch AT grouvenulrich ordinallogisticregressioninmedicalresearch |