A survey of models for repeated ordered categorical response data.

Abstract:

:We survey models for analysing repeated observations on an ordered categorical response variable. The models presented are univariate models that permit correlation among repeated measurements. The models describe simultaneously the dependence of marginal response distributions on values of explanatory variables and on the occasion of response. We present models for three transformations of the response distribution: cumulative logits, adjacent-category logits, and the mean for scores assigned to response categories. We discuss three methods for fitting the models: maximum likelihood, weighted least squares, and semi-parametric. Weighted least squares is easily implemented with SAS, as illustrated with a study designed to compare a drug with a placebo for the treatment of insomnia.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Agresti A

doi

10.1002/sim.4780081005

subject

Has Abstract

pub_date

1989-10-01 00:00:00

pages

1209-24

issue

10

eissn

0277-6715

issn

1097-0258

journal_volume

8

pub_type

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