Title: Practical inference from industrial split-plot designs
Authors: Goos, Peter ×
Langhans, Ivan
Vandebroek, Martina #
Issue Date: 2006
Series Title: Journal of Quality Technology vol:38 issue:2 pages:162-179
Abstract: In many industrial response surface experiments, some of the factors investigated are not reset independently. The resulting experimental design then is of the split-plot type, and the observations in the experiment are in many cases correlated. A proper analysis of the experimental data therefore is a mixed model analysis involving generalized least-squares estimation. Many people, however, analyze the data as if the experiment was completely randomized and estimate the model using ordinary least squares. The purposes of this article are to quantify the differences in conclusions reached from the two methods of analysis and to provide the reader with guidance for analyzing split-plot experiments in practice. The problem of determining the denominator degrees of freedom for significance tests in the mixed model analysis is discussed as well.
ISSN: 0022-4065
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science