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

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Bibliographic Details
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]
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Database: Psychology and Behavioral Sciences Collection
Description
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]
ISSN:00018244
DOI:10.1007/s10519-005-2791-5