Regression models for unconstrained, partially or fully constrained continuation odds ratios

• Published in: International journal of epidemiology Vol. 30; no. 6; pp. 1379 - 1382
• Main Authors: Cole, Stephen R, Ananth, Cande V
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.12.2001; Oxford Publishing Limited (England)
• Subjects: Biological and medical sciences; Continuation-ratio model; Epidemiologic Methods; epidemiological methods; Epidemiology; Episiotomy - adverse effects; General aspects; Humans; Infant, Newborn; Lacerations - epidemiology; Logistic Models; Medical sciences; Methodology; Odds Ratio; ordered response; Public health. Hygiene; Public health. Hygiene-occupational medicine; Human; Methodology; Regression model; Epidemiology; Statistical model; Public health
• ISSN: 0300-5771; 1464-3685; 1464-3685
• DOI: 10.1093/ije/30.6.1379

Epidemiologists frequently encounter studies with ordered responses. Standard ordered response logit models, such as the continuation ratio model, constrain exposure to have a homogenous effect across thresholds of the ordered response. We demonstrate a method for fitting regression models for unconstrained, partially or fully constrained continuation odds ratios using a ‘person-threshold’ data set. For each subject, we create a separate record for each response threshold the subject is ‘at risk’ of passing and then apply standard binary logistic regression to estimate the continuation-ratio model. An example demonstrates the unconstrained, partially and fully constrained continuation-ratio model, while a small simulation study examines some properties of the proposed ‘person-threshold’ approach. Finally, we present a brief discussion of statistical software to implement the method.