Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
2288547
TITLE
Alternative common factor models for multivariate biometric analyses.
ABSTRACT
In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide alternatives for the traditional biometric twin design. We use structural equations and path models to define biometric group differences, we write traditional common-factor models in the same way, and then we take a detailed look at some alternative multivariate and biometric models. We contrast the biometric-factors covariance structure approach used by Loehlin and Vandenberg (1968), Martin and Eaves (1977), and others with the psychometric-factors approach used by McArdle et al. (1980) and others. We use the multivariate primary mental abilities data on monozygotic (MZ) and dizygotic (DZ) twins from Loehlin and Vandenberg (1968) to detail fundamental differences in model specification and results. We extend both multivariate biometric approaches using exploratory and confirmatory multiple-factor models. These comparisons show that each alternative multivariate methodology has useful features for empirical applications.
DATE PUBLISHED
1990 Sep
HISTORY
PUBSTATUS PUBSTATUSDATE
pubmed 1990/09/01
medline 1990/09/01 00:01
entrez 1990/09/01 00:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
McArdle JJ McArdle J J JJ Department of Psychology, University of Virginia, Charlottesville 22903.
Goldsmith HH Goldsmith H H HH
INVESTIGATORS
JOURNAL
VOLUME: 20
ISSUE: 5
TITLE: Behavior genetics
ISOABBREVIATION: Behav. Genet.
YEAR: 1990
MONTH: Sep
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Print
ISSN: 0001-8244
ISSNTYPE: Print
MEDLINE JOURNAL
MEDLINETA: Behav Genet
COUNTRY: United States
ISSNLINKING: 0001-8244
NLMUNIQUEID: 0251711
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, U.S. Gov't, P.H.S.
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
AG02695 NIA NIH HHS United States
AG04704 NIA NIH HHS United States
AG07137 NIA NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Humans
Intelligence
Models, Genetic
Models, Statistical
Multivariate Analysis
Software
Twins psychology
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's