Detecting active effects in unreplicated designs

Angelopoulos, P; Koukouvinos, C

dc.contributor.author	Angelopoulos, P	en
dc.contributor.author	Koukouvinos, C	en
dc.date.accessioned	2014-03-01T01:28:08Z
dc.date.available	2014-03-01T01:28:08Z
dc.date.issued	2008	en
dc.identifier.issn	0266-4763	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18721
dc.subject	Effect	en
dc.subject	Factorial	en
dc.subject	Outliers	en
dc.subject	Unreplicated design	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	FACTORIAL-EXPERIMENTS	en
dc.subject.other	QUICK	en
dc.title	Detecting active effects in unreplicated designs	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/02664760701833008	en
heal.identifier.secondary	http://dx.doi.org/10.1080/02664760701833008	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Unreplicated factorial designs pose a difficult problem in analysis because there are no degrees of freedom left to estimate the error. Daniel [Technometrics 1 (1959), pp. 311-341] proposed an ingenious graphical method that does not require sigma to be estimated. Here we try to put Daniel's method into a formal framework and lift the subjectiveness that carries. A simulation study has been conducted that shows that the proposed method behaves better than Lenth's [Technometrics 31 (1989), pp. 469-473] popular method.	en
heal.publisher	ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD	en
heal.journalName	Journal of Applied Statistics	en
dc.identifier.doi	10.1080/02664760701833008	en
dc.identifier.isi	ISI:000256403200004	en
dc.identifier.volume	35	en
dc.identifier.issue	3	en
dc.identifier.spage	277	en
dc.identifier.epage	281	en