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Title:

A mixed autoregressive probit model for ordinal longitudinal data

Document type:
Zeitschriftenaufsatz
Author(s):
Varin, C. and Czado, C.
Abstract:
Longitudinal data with binary and ordinal outcomes routinely appear in medical applications. Existing methods are typically designed to deal with short measurement series. In contrast, modern longitudinal data can result in large numbers of subject-specific serial observations. In this framework, we consider multivariate probit models with random effects to capture heterogeneity and autoregressive terms for describing the serial dependence. Since likelihood inference for the proposed class...     »
Keywords:
Autoregressive residuals; Composite likelihood; Longitudinal data; Migraine severity; Ordinal probit; Mixed models; Pairwise likelihood.
Journal title:
Biostatistics
Year:
2009
Journal volume:
11
Year / month:
2009-11
Journal issue:
1
Pages contribution:
127-138
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1093/biostatistics/kxp042
Status:
Verlagsversion / published
Semester:
SS 10
Format:
Text
 BibTeX