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Titolo:
Detection of interactions in experiments on large numbers of factors
Autore:
Lewis, SM; Dean, AM;
Indirizzi:
Univ Southampton, Fac Math Studies, Southampton SO17 1BJ, Hants, England Univ Southampton Southampton Hants England SO17 1BJ 7 1BJ, Hants, England Ohio State Univ, Columbus, OH 43210 USA Ohio State Univ Columbus OH USA 43210 State Univ, Columbus, OH 43210 USA
Titolo Testata:
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
, volume: 63, anno: 2001,
parte:, 4
pagine: 633 - 659
SICI:
1369-7412(2001)63:<633:DOIIEO>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
SUPERSATURATED DESIGNS; 2-FACTOR INTERACTIONS; PARAMETER DESIGN; QUALITY-CONTROL; 2-LEVEL; CONSTRUCTION; SEARCH;
Keywords:
active effect; cancellation; factorial experiment; group screening; interactions;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
39
Recensione:
Indirizzi per estratti:
Indirizzo: Lewis, SM Univ Southampton, Fac Math Studies, Southampton SO17 1BJ, Hants,England Univ Southampton Southampton Hants England SO17 1BJ ts, England
Citazione:
S.M. Lewis e A.M. Dean, "Detection of interactions in experiments on large numbers of factors", J ROY STA B, 63, 2001, pp. 633-659

Abstract

One of the main advantages of factorial experiments is the information that they can offer on interactions. When there are many factors to be studied, some or all of this information is often sacrificed to keep the size of an experiment economically feasible. Two strategies for group screening are presented for a large number of factors, over two stages of experimentation, with particular emphasis on the detection of interactions. One approach estimates only main effects at the first stage (classical group screening), whereas the other new method (interaction group screening) estimates both main effects and key two-factor interactions at the first stage. Three criteria are used to guide the choice of screening technique, and also the size of the groups of factors for study in the first-stage experiment. The criteria seek to minimize the expected total number of observations In the experiment, the probability that the size of the experiment exceeds a prespecified target and the proportion of active individual factorial effects which are not detected. To Implement these criteria, results are derived on the relationship between the grouped and individual factorial effects, and the probability distributions of the numbers of grouped factors whose main effects or interactions are declared active at the first stage. Examples are usedto illustrate the methodology, and some issues and open questions for the practical implementation of the results are discussed.

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Documento generato il 02/07/20 alle ore 18:06:46