Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/353
Title: Marginal modelling of multivariate categorical data
Authors: MOLENBERGHS, Geert 
LESAFFRE, Emmanuel 
Issue Date: 1999
Publisher: JOHN WILEY
Source: Statistics in Medicine, 18(17-18). p. 2237-2255
Abstract: This paper describes likelihood methods of analysis for multivariate categorical data. The joint distribution is specified in terms of marginal mean functions, and pairwise and higher order association measures. For the association, the emphasis is on global odds ratios. The method allows flexible formulation of a broad class of designs, such as repeated measurements, longitudinal studies, interrater agreement and cross-over trials. The proposed model can be used for parameter estimation and hypothesis testing. Simple fitting algorithms are proposed. The method is illustrated using a data example.
Document URI: http://hdl.handle.net/1942/353
Link to publication: https://lirias.kuleuven.be/bitstream/123456789/26770/1/7516.pdf
ISSN: 0277-6715
e-ISSN: 1097-0258
DOI: 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2237::AID-SIM252>3.0.CO;2-R
ISI #: 000082507800005
Rights: Copyright (c) 1999 John Wiley & Sons, Ltd
Type: Journal Contribution
Validations: ecoom 2000
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
Molenberghs_et_al-1999-Statistics_in_Medicine.pdfPublished version169.14 kBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

43
checked on Sep 5, 2020

WEB OF SCIENCETM
Citations

36
checked on May 22, 2022

Page view(s)

46
checked on May 25, 2022

Download(s)

90
checked on May 25, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.