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.

journal_name

Int J Epidemiol

authors

Cole SR,Ananth CV

doi

10.1093/ije/30.6.1379

keywords:

subject

Has Abstract

pub_date

2001-12-01 00:00:00

pages

1379-82

issue

6

eissn

0300-5771

issn

1464-3685

journal_volume

30

pub_type

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