Publication
Title
Group screening method for the statistical analysis of E(f_NOD)optimal mixed-level supersaturated designs
Author
Abstract
In this paper, we propose the application of group screening methods for analyzing data using E.fNOD/-optimal mixed-level supersaturated designs possessing the equal occurrence property. Supersaturated designs are a large class of factorial designs which can be used for screening out the important factors from a large set of potentially active variables. The huge advantage of these designs is that they reduce the experimental cost drastically, but their critical disadvantage is the high degree of confounding among factorial effects. Based on the idea of the group screening methods, the f factors are sub-divided into g ``group-factors''. The ``group-factors'' are then studied using the penalized likelihood statistical analysis methods at a factorial design with orthogonal or near-orthogonal columns. All factors in groups found to have a large effect are then studied in a second stage of experiments. A comparison of the Type I and Type II error rates of various estimation methods via simulation experiments is performed. The results are presented in tables and discussion follows.
Language
English
Source (journal)
Statistical methodology. - Place of publication unknown
Publication
Place of publication unknown : 2009
ISSN
1572-3127
Volume/pages
6:4(2009), p. 380-388
Full text (Publishers DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
External links
Record
Identification
Creation 17.05.2010
Last edited 21.11.2016