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Article: A maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data

TitleA maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data
Authors
KeywordsDiallel cross
inbred strains
incomplete diallel
maximum likelihood
model-fitting
Issue Date1993
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244
Citation
Behavior Genetics, 1993, v. 23 n. 1, p. 69-76 How to Cite?
AbstractA method is presented for conducting a Hayman analysis of non-replicated diallel tables using a maximum-likelihood (ML) model-fitting approach, rather than a traditional analysis of variance (ANOVA) approach. Hayman's linear model for a diallel analysis is used to generate a table of expected cell means. This table of expected cell means is fit to a table of observed cell means, and the fit is assessed using a chi-square value. Often data collected from diallel crosses fail to meet the underlying assumptions of ANOVA. The ML method makes no assumptions about equal cell sizes or homogeneity of variance. Thus, the ML method for diallel analysis provides some statistical advantages over ANOVA methods. The ML method also offers the advantage of having the ability to analyze diallels with missing cells. Using the ML method, incomplete diallel tables can be analyzed, and the partitioning of all the sources of variation in a diallel table is still accomplished from the remaining crosses. These advantages make the ML method an attractive approach for extracting the maximum amount of information from a diallel table.
Persistent Identifierhttp://hdl.handle.net/10722/143687
ISSN
2015 Impact Factor: 3.268
2015 SCImago Journal Rankings: 1.457
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorRodriguez, LAen_HK
dc.contributor.authorFulker, DWen_HK
dc.contributor.authorCherny, SSen_HK
dc.date.accessioned2011-12-16T08:09:30Z-
dc.date.available2011-12-16T08:09:30Z-
dc.date.issued1993en_HK
dc.identifier.citationBehavior Genetics, 1993, v. 23 n. 1, p. 69-76en_HK
dc.identifier.issn0001-8244en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143687-
dc.description.abstractA method is presented for conducting a Hayman analysis of non-replicated diallel tables using a maximum-likelihood (ML) model-fitting approach, rather than a traditional analysis of variance (ANOVA) approach. Hayman's linear model for a diallel analysis is used to generate a table of expected cell means. This table of expected cell means is fit to a table of observed cell means, and the fit is assessed using a chi-square value. Often data collected from diallel crosses fail to meet the underlying assumptions of ANOVA. The ML method makes no assumptions about equal cell sizes or homogeneity of variance. Thus, the ML method for diallel analysis provides some statistical advantages over ANOVA methods. The ML method also offers the advantage of having the ability to analyze diallels with missing cells. Using the ML method, incomplete diallel tables can be analyzed, and the partitioning of all the sources of variation in a diallel table is still accomplished from the remaining crosses. These advantages make the ML method an attractive approach for extracting the maximum amount of information from a diallel table.en_HK
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244en_HK
dc.relation.ispartofBehavior Geneticsen_HK
dc.subjectDiallel crossen_HK
dc.subjectinbred strainsen_HK
dc.subjectincomplete diallelen_HK
dc.subjectmaximum likelihooden_HK
dc.subjectmodel-fittingen_HK
dc.titleA maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing dataen_HK
dc.typeArticleen_HK
dc.identifier.emailCherny, SS: cherny@hku.hken_HK
dc.identifier.authorityCherny, SS=rp00232en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.pmid8476393-
dc.identifier.scopuseid_2-s2.0-0027515975en_HK
dc.identifier.volume23en_HK
dc.identifier.issue1en_HK
dc.identifier.spage69en_HK
dc.identifier.epage76en_HK
dc.identifier.isiWOS:A1993KV41400006-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridRodriguez, LA=16647132600en_HK
dc.identifier.scopusauthoridFulker, DW=7005792286en_HK
dc.identifier.scopusauthoridCherny, SS=7004670001en_HK

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