Biometrical Modeling of Twin and Family Data Using Standard Mixed Model Software

@article{citeulike:1367507, abstract = {Abstract: Biometrical genetic modeling of twin or other family data can be used to decompose the variance of an observed response or 'phenotype' into genetic and environmental components. Convenient parameterizations requiring few random effects are proposed, which allow such models to be estimated using widely available software for linear mixed models (continuous phenotypes) or generalized linear mixed models (categorical phenotypes). We illustrate the proposed approach by modeling family data on the continuous phenotype birth weight and twin data on the dichotomous phenotype depression. The example data sets and commands for Stata and R/S-PLUS are available at the Biometrics website.}, address = {Graduate School of Education \& Graduate Group in Biostatistics, University of California, Berkeley, California 94720, U.S.A. \& Institute of Education, University of London, London WC1H OAL, U.K.}, author = {Rabe-Hesketh, S. and Skrondal, A. and Gjessing, H. K. K. }, citeulike-article-id = {1367507}, doi = {http://dx.doi.org/10.1111/j.1541-0420.2007.00803.x}, issn = {0006-341X}, journal = {Biometrics}, keywords = {genetics, mixed-model}, month = {May}, posted-at = {2008-04-03 10:21:36}, priority = {2}, title = {Biometrical Modeling of Twin and Family Data Using Standard Mixed Model Software}, url = {http://dx.doi.org/10.1111/j.1541-0420.2007.00803.x}, year = {2007} }

TY - JOUR ID - citeulike:1367507 L3 - citeulike-article-id:1367507 TI - Biometrical Modeling of Twin and Family Data Using Standard Mixed Model Software JF - Biometrics AD - Graduate School of Education & Graduate Group in Biostatistics, University of California, Berkeley, California 94720, U.S.A. & Institute of Education, University of London, London WC1H OAL, U.K. SN - 0006-341X N2 - Abstract: Biometrical genetic modeling of twin or other family data can be used to decompose the variance of an observed response or 'phenotype' into genetic and environmental components. Convenient parameterizations requiring few random effects are proposed, which allow such models to be estimated using widely available software for linear mixed models (continuous phenotypes) or generalized linear mixed models (categorical phenotypes). We illustrate the proposed approach by modeling family data on the continuous phenotype birth weight and twin data on the dichotomous phenotype depression. The example data sets and commands for Stata and R/S-PLUS are available at the Biometrics website. KW - genetics KW - mixed-model AU - Rabe-Hesketh, S AU - Skrondal, A AU - Gjessing, HKK PY - 2007/05/02/ UR - http://dx.doi.org/10.1111/j.1541-0420.2007.00803.x ER -