Generalized Symmetry Models for Hypercubic Concordance Tables

Gianfranco Lovison

International Statistical Review, 2000, vol. 68, issue 3, 323-338

Abstract: Frequency data obtained classifying a sample of ‘units’ by the same categorical variable repeatedly over ‘components’, can be arranged in a hypercubic concordance table (h.c.t.). This kind of data naturally arises in a number of different areas such as longitudinal studies, studies using matched and clustered data, item‐response analysis, agreement analysis. In spite of the substantial diversity of the mechanisms that can generate them, data arranged in a h.c.t. can all be analyzed via models of symmetry and quasi‐symmetry, which exploit the special structure of the h.c.t. The paper extends the definition of such models to any dimension, introducing the class of generalized symmetry models, which provides a unified framework for inference on categorical data that can be represented in a h.c.t., Within this framework it is possible to derive the common structure which underlies these models and clarify their meaning; their usefulness in applied work is illustrated by a re‐analysis of two real examples.

Date: 2000
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/j.1751-5823.2000.tb00334.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:68:y:2000:i:3:p:323-338

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0306-7734

Access Statistics for this article

International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg

More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().