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- Publisher Website: 10.1007/BF01067555
- Scopus: eid_2-s2.0-0027515975
- PMID: 8476393
- WOS: WOS:A1993KV41400006
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Article: A maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data
Title | A maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data |
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Authors | |
Keywords | Diallel cross inbred strains incomplete diallel maximum likelihood model-fitting |
Issue Date | 1993 |
Publisher | Springer 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? |
Abstract | A 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 Identifier | http://hdl.handle.net/10722/143687 |
ISSN | 2023 Impact Factor: 2.6 2023 SCImago Journal Rankings: 1.092 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Rodriguez, LA | en_HK |
dc.contributor.author | Fulker, DW | en_HK |
dc.contributor.author | Cherny, SS | en_HK |
dc.date.accessioned | 2011-12-16T08:09:30Z | - |
dc.date.available | 2011-12-16T08:09:30Z | - |
dc.date.issued | 1993 | en_HK |
dc.identifier.citation | Behavior Genetics, 1993, v. 23 n. 1, p. 69-76 | en_HK |
dc.identifier.issn | 0001-8244 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/143687 | - |
dc.description.abstract | A 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.publisher | Springer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244 | en_HK |
dc.relation.ispartof | Behavior Genetics | en_HK |
dc.subject | Diallel cross | en_HK |
dc.subject | inbred strains | en_HK |
dc.subject | incomplete diallel | en_HK |
dc.subject | maximum likelihood | en_HK |
dc.subject | model-fitting | en_HK |
dc.title | A maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Cherny, SS: cherny@hku.hk | en_HK |
dc.identifier.authority | Cherny, SS=rp00232 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/BF01067555 | - |
dc.identifier.pmid | 8476393 | - |
dc.identifier.scopus | eid_2-s2.0-0027515975 | en_HK |
dc.identifier.volume | 23 | en_HK |
dc.identifier.issue | 1 | en_HK |
dc.identifier.spage | 69 | en_HK |
dc.identifier.epage | 76 | en_HK |
dc.identifier.isi | WOS:A1993KV41400006 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Rodriguez, LA=16647132600 | en_HK |
dc.identifier.scopusauthorid | Fulker, DW=7005792286 | en_HK |
dc.identifier.scopusauthorid | Cherny, SS=7004670001 | en_HK |
dc.identifier.issnl | 0001-8244 | - |