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 interpretation 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.
Bender
R
R
Department of Metabolic Diseases and Nutrition, Heinrich-Heine-University of Düsseldorf.
Grouven
U
U
D000704:Analysis of Variance; D003930:Diabetic Retinopathy / Q000378:metabolism; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D016015:Logistic Models; D008297:Male; D016017:Odds Ratio; D016016:Proportional Hazards Models; D012107:Research Design
D006442:Glycated Hemoglobin