The University of Southampton
University of Southampton Institutional Repository

A general strategy for analyzing data from split-plot and multistratum experimental designs

A general strategy for analyzing data from split-plot and multistratum experimental designs
A general strategy for analyzing data from split-plot and multistratum experimental designs
Increasingly, industrial experiments use multistratum designs, such as split-plot and strip-plot designs. Often, these experiments span more than one processing stage. The challenge is to identify an appropriate multistratum design, along with an appropriate statistical model. In this article, we introduce Hasse diagrams in the response surface context as a tool to visualize the unit structure of the experimental design, the randomization and sampling approaches used, the stratum in which each experimental factor is applied, and the degrees of freedom available in each stratum to estimate main effects, interactions, and variance components. We illustrate their use on several responses measured in a large study of the adhesion properties of coatings to polypropylene. We discuss quantitative, binary, and ordered categorical responses, for designs ranging from a simple split-plot to a strip-plot that involves repeated measurements of the response. The datasets discussed in this article are available online as supplementary materials, along with sample SAS programs.
0040-1706
340-354
Goos, Peter
e85ac472-9312-4a77-ba77-b2f21b64f39e
Gilmour, Steven G.
984dbefa-893b-444d-9aa2-5953cd1c8b03
Goos, Peter
e85ac472-9312-4a77-ba77-b2f21b64f39e
Gilmour, Steven G.
984dbefa-893b-444d-9aa2-5953cd1c8b03

Goos, Peter and Gilmour, Steven G. (2012) A general strategy for analyzing data from split-plot and multistratum experimental designs. Technometrics, 54 (4), 340-354. (doi:10.1080/00401706.2012.694777).

Record type: Article

Abstract

Increasingly, industrial experiments use multistratum designs, such as split-plot and strip-plot designs. Often, these experiments span more than one processing stage. The challenge is to identify an appropriate multistratum design, along with an appropriate statistical model. In this article, we introduce Hasse diagrams in the response surface context as a tool to visualize the unit structure of the experimental design, the randomization and sampling approaches used, the stratum in which each experimental factor is applied, and the degrees of freedom available in each stratum to estimate main effects, interactions, and variance components. We illustrate their use on several responses measured in a large study of the adhesion properties of coatings to polypropylene. We discuss quantitative, binary, and ordered categorical responses, for designs ranging from a simple split-plot to a strip-plot that involves repeated measurements of the response. The datasets discussed in this article are available online as supplementary materials, along with sample SAS programs.

Text
Technometrics_2012.pdf - Accepted Manuscript
Restricted to Repository staff only
Request a copy

More information

e-pub ahead of print date: 29 May 2012
Organisations: Statistics

Identifiers

Local EPrints ID: 348387
URI: http://eprints.soton.ac.uk/id/eprint/348387
ISSN: 0040-1706
PURE UUID: e7a11471-f7e4-403d-8364-d4c67235c424

Catalogue record

Date deposited: 13 Feb 2013 11:19
Last modified: 14 Mar 2024 12:58

Export record

Altmetrics

Contributors

Author: Peter Goos
Author: Steven G. Gilmour

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.

×