title: Regression models for unconstrained, partially or fully constrained continuation odds ratios.
abstract: Epidemiologists frequently encounter studies with ordered responses. Standard ordered response logit models, such as the continuation ratio model, constrain exposure to have a homogeneous 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.
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD 21205, USA. scole@jhsph.edu
authors.forename: S R
authors.initials: SR
authors.lastname: Cole
authors.forename: C V
authors.initials: CV
authors.lastname: Ananth
mesh_terms: D004812:Epidemiologic Methods; D004841:Episiotomy / Q000009:adverse effects; D006801:Humans; D007231:Infant, Newborn; D022125:Lacerations / Q000453:epidemiology; D016015:Logistic Models; D016017:Odds Ratio