Modelling Strategies for Repeated Multiple Response Data. (28th August 2013)

• Record Type: Journal Article
• Authors: Suesse, Thomas; Liu, Ivy
• Is Part Of: International statistical review. Volume 81:Number 2(2013:Aug.)
• Page Start: 230
• Page End: 248
• Publication Date: 2013-08-28
• Subjects: Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12015
• Languages: English
• ISSNs: 0306-7734

Abstract

<abstract abstract-type="main" id="insr12015-abs-0001"> <title>Summary</title> <p id="insr12015-para-0001">This article discusses modelling strategies for repeated measurements of multiple response variables. Such data arise in the context of categorical variables where one can select more than one of the categories as the response. We consider each of the multiple responses as a binary outcome and use a marginal (or population‐averaged) modelling approach to analyse its means. Generalized estimating equations are used to account for different correlation structures, both over time and between items. We also discuss an alternative approach using a generalized linear mixed model with conditional interpretations. We illustrate the methods using data from a panel study in Australia called the Household, Income, and Labour Dynamics Survey.</p> </abstract>