regression models for ordinal responses a review of methods

Conclusions this paper presents a synthesized review

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Unformatted text preview: research. Conclusions. This paper presents a synthesized review of generalized linear regression models for analysing ordered responses. We recommend that the analyst performs (i) goodness-of-fit tests and an analysis of residuals, (ii) sensitivity analysis by fitting and comparing different models, and (iii) by graphically examining the model assumptions. Keywords: Multinomial probabilities, ordinal models, cumulative logit model, continuation-ratio model, partial-proportional odds model, polytomous logistic model, stereotype logistic model trial of a single-dose, post-operative analgesic clinical trial.2 A series of four drugs, denoted by C15, C60, Z100, and EC4 were randomized to patients. The patient responses to the drug were recorded on a fivelevel ordinal scale (poor, fair, good, very good and excellent). Counts for the most favourable responses, ‘very good’ and ‘excellent’, were amalgamated into one category (‘very good’) due to sparse cell counts. The two drugs Z100 and EC4 were found to be quite similar and together rated better...
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