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Article: Logistic regression analysis of twin data: Estimation of parameters of the multifactorial liability-threshold model

TitleLogistic regression analysis of twin data: Estimation of parameters of the multifactorial liability-threshold model
Authors
Issue Date1994
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, 1994, v. 24 n. 3, p. 229-238 How to Cite?
AbstractWe extend the DeFries-Fulker regression model for the analysis of quantitative twin data to cover binary traits and genetic dominance. In the proposed logistic regression model, the cotwin's trait status, C, is the response variable, while the proband's trait status, P, is a predictor variable coded as k (affected) and 0 (unaffected). Additive genetic effects are modeled by the predictor variable PR, which equals P for monozygotic (MZ) and P/2 for dizygotic (DZ) twins; and dominant genetic effects, by PD, which equals P for MZ and P/4 for DZ twins. By setting an appropriate scale for P (i.e., the value of k), the regression coefficients of P, PR, and PD are estimates of the proportions of variance in liability due to common family environment, additive genetic effects, and dominant genetic effects, respectively, for a multifactorial liability-threshold model. This model was applied to data on lifetime depression from the Virginia Twin Registry and produced results similar to those from structural equation modeling.
Persistent Identifierhttp://hdl.handle.net/10722/175704
ISSN
2015 Impact Factor: 3.268
2015 SCImago Journal Rankings: 1.457
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSham, PCen_US
dc.contributor.authorWalters, EEen_US
dc.contributor.authorNeale, MCen_US
dc.contributor.authorHeath, ACen_US
dc.contributor.authorMaclean, CJen_US
dc.contributor.authorKendler, KSen_US
dc.date.accessioned2012-11-26T09:00:37Z-
dc.date.available2012-11-26T09:00:37Z-
dc.date.issued1994en_US
dc.identifier.citationBehavior Genetics, 1994, v. 24 n. 3, p. 229-238en_US
dc.identifier.issn0001-8244en_US
dc.identifier.urihttp://hdl.handle.net/10722/175704-
dc.description.abstractWe extend the DeFries-Fulker regression model for the analysis of quantitative twin data to cover binary traits and genetic dominance. In the proposed logistic regression model, the cotwin's trait status, C, is the response variable, while the proband's trait status, P, is a predictor variable coded as k (affected) and 0 (unaffected). Additive genetic effects are modeled by the predictor variable PR, which equals P for monozygotic (MZ) and P/2 for dizygotic (DZ) twins; and dominant genetic effects, by PD, which equals P for MZ and P/4 for DZ twins. By setting an appropriate scale for P (i.e., the value of k), the regression coefficients of P, PR, and PD are estimates of the proportions of variance in liability due to common family environment, additive genetic effects, and dominant genetic effects, respectively, for a multifactorial liability-threshold model. This model was applied to data on lifetime depression from the Virginia Twin Registry and produced results similar to those from structural equation modeling.en_US
dc.languageengen_US
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244en_US
dc.relation.ispartofBehavior Geneticsen_US
dc.subject.meshAdulten_US
dc.subject.meshDepressive Disorder - Genetics - Psychologyen_US
dc.subject.meshDiseases In Twins - Genetics - Psychologyen_US
dc.subject.meshFemaleen_US
dc.subject.meshGenes, Dominanten_US
dc.subject.meshHumansen_US
dc.subject.meshLogistic Modelsen_US
dc.subject.meshMaleen_US
dc.subject.meshMiddle Ageden_US
dc.subject.meshModels, Geneticen_US
dc.subject.meshVirginiaen_US
dc.titleLogistic regression analysis of twin data: Estimation of parameters of the multifactorial liability-threshold modelen_US
dc.typeArticleen_US
dc.identifier.emailSham, PC: pcsham@hku.hken_US
dc.identifier.authoritySham, PC=rp00459en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/BF01067190en_US
dc.identifier.pmid7945153-
dc.identifier.scopuseid_2-s2.0-0028287874en_US
dc.identifier.volume24en_US
dc.identifier.issue3en_US
dc.identifier.spage229en_US
dc.identifier.epage238en_US
dc.identifier.isiWOS:A1994NX84100004-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridSham, PC=34573429300en_US
dc.identifier.scopusauthoridWalters, EE=7102865802en_US
dc.identifier.scopusauthoridNeale, MC=35418917800en_US
dc.identifier.scopusauthoridHeath, AC=7201835346en_US
dc.identifier.scopusauthoridMacLean, CJ=7102972772en_US
dc.identifier.scopusauthoridKendler, KS=35396760800en_US

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