International Journal of Epidemiology, Vol 26, 1323-1333, Copyright © 1997 by International Epidemiological Association
CV Ananth and DG Kleinbaum
BACKGROUND: Epidemiologists are often interested in estimating the risk of
several related diseases as well as adverse outcomes, which have a natural
ordering of severity or certainty. While most investigators choose to model
several dichotomous outcomes (such as very low birthweight versus normal
and moderately low birthweight versus normal), this approach does not fully
utilize the available information. Several statistical models for ordinal
responses have been proposed, but have been underutilized. In this paper,
we describe statistical methods for modelling ordinal response data, and
illustrate the fit of these models to a large database from a perinatal
health programme. METHODS: Models considered here include (1) the
cumulative logit model, (2) continuation-ratio model, (3) constrained and
unconstrained partial proportional odds models, (4) adjacent-category logit
model, (5) polytomous logistic model, and (6) stereotype logistic model. We
illustrate and compare the fit of these models on a perinatal database, to
study the impact of midline episiotomy procedure on perineal lacerations
during labour and delivery. Finally, we provide a discussion on graphical
methods for the assessment of model assumptions and model constraints, and
conclude with a discussion on the choice of an ordinal model. The primary
focus in this paper is the formulation of ordinal models, interpretation of
model parameters, and their implications for epidemiological 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.
ARTICLES
Regression models for ordinal responses: a review of methods and applications
Department of Obstetrics, Gynecology and Reproductive Sciences, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick 08901-1977, USA.
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