The University of Southampton
University of Southampton Institutional Repository

Split-plot designs: a useful tool for the statistical analysis of real medical data and repeated measurement problems

Split-plot designs: a useful tool for the statistical analysis of real medical data and repeated measurement problems
Split-plot designs: a useful tool for the statistical analysis of real medical data and repeated measurement problems
In this article, a split-plot design is applied for the collection of real medical data concerning biochemical and vital measurements of 283 patients in Intensive Care Unit, on a repeated measurement problem. Practical limitations and issues related to cost reveals frequently the practical usefulness of split-plot designs. When an experiment is planned, factors that are difficult or time consuming to manipulate appear and make complete randomization impractical. A split-plot structure is used when it is impractical to change the levels of some of the experimental factors. Our dataset, selected with the aid of a split-plot design, consists of 2256 observations 17 factors and 8 repetitions. A statistical analysis on the resulting data is performed and useful biological justification of our results is provided.
0973-7022
61-66
Koukouvinos, C.
3c626a53-575f-4c62-9b9a-a949f717764b
Lygkoni, E.
dddc0cfa-6ae3-416b-a52a-cb17944124ed
Mylona, K.
b44af287-2d9f-4df8-931c-32d8ab117864
Koukouvinos, C.
3c626a53-575f-4c62-9b9a-a949f717764b
Lygkoni, E.
dddc0cfa-6ae3-416b-a52a-cb17944124ed
Mylona, K.
b44af287-2d9f-4df8-931c-32d8ab117864

Koukouvinos, C., Lygkoni, E. and Mylona, K. (2009) Split-plot designs: a useful tool for the statistical analysis of real medical data and repeated measurement problems. Bulletin of Statistics & Economics, 3 (S09), Spring Issue, 61-66.

Record type: Article

Abstract

In this article, a split-plot design is applied for the collection of real medical data concerning biochemical and vital measurements of 283 patients in Intensive Care Unit, on a repeated measurement problem. Practical limitations and issues related to cost reveals frequently the practical usefulness of split-plot designs. When an experiment is planned, factors that are difficult or time consuming to manipulate appear and make complete randomization impractical. A split-plot structure is used when it is impractical to change the levels of some of the experimental factors. Our dataset, selected with the aid of a split-plot design, consists of 2256 observations 17 factors and 8 repetitions. A statistical analysis on the resulting data is performed and useful biological justification of our results is provided.

This record has no associated files available for download.

More information

Published date: 2009
Organisations: Statistics

Identifiers

Local EPrints ID: 336716
URI: http://eprints.soton.ac.uk/id/eprint/336716
ISSN: 0973-7022
PURE UUID: d5fe37ce-8298-49b9-a01f-8aba92f6ca73

Catalogue record

Date deposited: 04 Apr 2012 14:19
Last modified: 11 Dec 2021 00:04

Export record

Contributors

Author: C. Koukouvinos
Author: E. Lygkoni
Author: K. Mylona

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×