Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data.

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Title: Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data.
Authors: Posthuma, D., Boomsma, D. I.
Source: Behavior Genetics. Jul2005, Vol. 35 Issue 4, p499-505. 7p.
Subjects: Twins, Genetic markers, Genetic epidemiology, Genes, Sex differences (Biology), Integrated software
Abstract: Structural equation modeling (SEM) provides a flexible tool to carry out genetic analyses of family and twin data. The basic model which decomposes the variance between and within families for a particular trait into genetic and non-genetic components can be generalized to multivariate and/ or longitudinal data, incorporate sex differences in parameter estimates, and model the effects of measured environment, candidate genes or DNA marker data. We introduce a web-based library () of scripts for uni- and multivariate genetic epidemiological analyses, as well as for linkage and genetic association tests. The scripts are written to be used with the freely available software package Mx and provide a flexible and uniform approach to the analysis of data from relatives. [ABSTRACT FROM AUTHOR]
Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data.
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  Data: <searchLink fieldCode="DE" term="%22Twins%22">Twins</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+markers%22">Genetic markers</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+epidemiology%22">Genetic epidemiology</searchLink><br /><searchLink fieldCode="DE" term="%22Genes%22">Genes</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+differences+%28Biology%29%22">Sex differences (Biology)</searchLink><br /><searchLink fieldCode="DE" term="%22Integrated+software%22">Integrated software</searchLink>
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  Data: Structural equation modeling (SEM) provides a flexible tool to carry out genetic analyses of family and twin data. The basic model which decomposes the variance between and within families for a particular trait into genetic and non-genetic components can be generalized to multivariate and/ or longitudinal data, incorporate sex differences in parameter estimates, and model the effects of measured environment, candidate genes or DNA marker data. We introduce a web-based library () of scripts for uni- and multivariate genetic epidemiological analyses, as well as for linkage and genetic association tests. The scripts are written to be used with the freely available software package Mx and provide a flexible and uniform approach to the analysis of data from relatives. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Genetic epidemiology
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      – SubjectFull: Sex differences (Biology)
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      – SubjectFull: Integrated software
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      – TitleFull: Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data.
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