Statistical Methods in Medical Research

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
0962280206071845v1
16/6/497    most recent
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ibáñez, M.V.
Right arrow Articles by Simó, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ibáñez, M.V.
Right arrow Articles by Simó, A.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
This version was published on December 1, 2007
Statistical Methods in Medical Research, Vol. 16, No. 6, 497-522 (2007)
DOI: 10.1177/0962280206071845

Spatio-temporal modeling of perimetric test data

M.V. Ibáñez

Department of Mathematics, University Jaume I, Castellón, Spain, mibanez{at}mat.uji.es

A. Simó

Department of Mathematics, University Jaume I, Castellón, Spain

This work describes the application of a spatio-temporal modeling to the study of glaucoma, a very serious ocular illness. The aim of this modeling is to solve various significant medical problems, namely the forecasting of future observations, the classification of observations as normal or defective, and the simulation of new longitudinal data sets. In order to ascertain whether a patient suffers from glaucoma, a perimetry is performed. The output of a perimetry is called a visual field and consists of a map with 52 numerical values plotted on a regular grid. In this work, a data set of healthy patients' visual fields is used. The work begins with an exploratory spatial data analysis. A semi-parametric approach is used to model the mean, and the variogram is fitted using a Matérn function. Once the spatial structure has been analysed, the spatial mean is subtracted from all the observations in the data set and the spatio-temporal correlation of the residuals is explored. All this information is used to build a space-time model, the parameters of which are estimated by maximum likelihood. Different methods are used to check the goodness of fit.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?