regression models for ordinal responses a review of methods

C log odds ratios involve comparisons between poor

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Unformatted text preview: vourable responses very good and excellent are amalgamated. c Log-odds ratios involve comparisons between (‘poor’ versus ‘fair’), ( b there is perfect homogeneity within the categories being collapsed), typically resulting in a considerable loss of statistical power. Although several statistical models for ordinal responses have been proposed, their utilization in the epidemiological and biomedical literature has been minimal. The purpose of this paper is twofold: first, to provide a synthesized review of models for analysing data with ordinal responses, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Ordinal models that are considered include (1) cumulative logit or the ‘grouped continuous’ model,3,4 (2) continuationmodel,5 (3) constrained and unconstrained partial proportional odds models,6 (4) polytomous logistic model,7,8 (5) adjacent-category logistic model,9 and (6) stereotype logistic model.10 The development of each model is described in detail,...
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This document was uploaded on 02/25/2014.

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