Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: John Lawson, G. Bruce Schaalje, Bruce Jay Collings
Title: Blocking Mixed-Level Factorials with SAS
Abstract: Orthogonal array screening designs for mixed-level or asymmetric factorials have recently become popular. Tables of designs and software for creating these designs are readily available to practitioners. However, confounded block designs for mixed-level factorials are not as popular partly due to the fact that software for creating these designs has not been well publicized. Classical methods for creating confounded-block mixed-level factorials normally described in textbooks utilize modular arithmetic or finite fields. In the recent literature optimal design theory has also been proposed as method for creating these designs. Although no examples are shown in the online documentation, both classical and optimal confounded-block mixed-level factorials can be easily created using SAS data step programming in conjunction with proc plan, proc factex or proc optex. In this article we show examples of creating these designs in SAS, and we compare the properties of designs created by classical methods and optimal design theory.

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Paper: Blocking Mixed-Level Factorials with SAS     Download PDF (Downloads: 7442)
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DOI: 10.18637/jss.v032.c01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.