Mx Scripts Library: Structural Equation Modeling Scripts for Twin and Family Data
- 1 July 2005
- journal article
- research article
- Published by Springer Nature in Behavior Genetics
- Vol. 35 (4) , 499-505
- https://doi.org/10.1007/s10519-005-2791-5
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 (http://www.psy.vu.nl/mxbib) 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.Keywords
This publication has 21 references indexed in Scilit:
- Linkage analysis of smoking initiation and quantity in Dutch sibling pairsThe Pharmacogenomics Journal, 2004
- A Genome Scan for Eye Color in 502 Twin Families: Most Variation is due to a QTL on Chromosome 15qTwin Research, 2004
- Merlin—rapid analysis of dense genetic maps using sparse gene flow treesNature Genetics, 2001
- A note on computing the chi-square noncentrality parameter for power analysesBehavior Genetics, 1988
- Using LISREL to analyze genetic and environmental covariance structureBehavior Genetics, 1986
- Education policy and the heritability of educational attainmentNature, 1985
- A model for sibling effects in manHeredity, 1976
- A method for analyzing the genetic basis of covariationBehavior Genetics, 1974
- Comparison of the biometrical genetical, MAVA, and classical approaches to the analysis of the human behavior.Psychological Bulletin, 1970
- THE GENETIC ANALYSIS OF CONTINUOUS VARIATION: A COMPARISON OF EXPERIMENTAL DESIGNS APPLICABLE TO HUMAN DATABritish Journal of Mathematical and Statistical Psychology, 1969