All:
(Non-geometric) Plackett-Burman designs have the very interesting property
that they are "3-projectable." This means that for ANY subset of 3
variables, the design contains a full factorial (+ one or more 1/2
fractions) in those 3 variables.. This was proven during the 1990's by Wu,
Lin, Box, Tyssedal, Chen and colleagues in a series of papers. This means
that there is an alternative method (and philosophy of) analysis: Consider
fits in all possible subsets of 3 variables and pick the (few?) best. This
allows for higher order interactions under the assumption of parsimony --
that only up to 3 of the variables are needed to give a good fit. Box and
Tyssedal discuss this in their paper (about 1996 , I think). I have in fact
used this approach for screening designs and it generally works quite well
(though not infallibly, of course, as (partial) confounding rears its head
in other ways).
Cheers,
Bert Gunter
Biometrics Research RY 33-300
Merck & Company
P.O. Box 2000
Rahway, NJ 07065-0900
Phone: (732) 594-7765
mailto: bert_gunter@merck.com
"The business of the statistician is to catalyze the scientific learning
process." -- George E.P. Box
-----Original Message-----
From: Spencer Graves [mailto:spencer.graves@pdf.com]
Sent: Wednesday, October 22, 2003 10:17 AM
To: Firat ÖZDEMIR
Cc: s-news@wubios.wustl.edu
Subject: Re: [S] plackett burman design
Have you tried searching "www.google.com" for "Plackett-Burman
design"? I just got several hits there.
Most modern books on experimental design, e.g., Box, Hunter,
Hunter (1978) Statistics for Experimenters (Wiley) describe
Plackett-Burman designs and cite Plackett and Burman's original paper.
As far as I know, the standard analysis involves computing coefficients
for a saturated model (or "effects" = twice the corresponding regression
coefficient) and making a normal probability plot of those numbers.
Points obviously off the line are considered to be statistically
significant. A gap in the middle or an offset from mean 0 indicate an
outlier (Box on Quality and Discovery, Wiley, 2000). Wu and Hamada
(2000) Experiments (Wiley) recommend an advanced stepwise regression.
I've developed S-Plus code for my version of advanced stepwise
regression, downloadable from "www.prodsyse.com".
Hope this helps. spencer graves
Fırat ÖZDEMİR wrote:
> is there any paper, web page or something else available where I
> can have detailed information on analysis of plackett-burman designs
>
> firat.ozdemir@deu.edu.tr <mailto:firat.ozdemir@deu.edu.tr>
>
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