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Modeling Extended Twin Family Data I: Description of the Cascade Model

Published online by Cambridge University Press:  21 February 2012

Matthew C. Keller*
Affiliation:
Department of Psychology, University of Colorado at Boulder, United States of America; Institute for Behavioral Genetics, University of Colorado at Boulder, United States of America. [email protected]
Sarah E. Medland
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, United States of America.
Laramie E. Duncan
Affiliation:
Department of Psychology, University of Colorado at Boulder, United States of America.
Peter K. Hatemi
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, United States of America.
Michael C. Neale
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, United States of America.
Hermine H. M. Maes
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, United States of America.
Lindon J. Eaves
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, United States of America.
*
*Address for correspondence: Matthew C. Keller, Department of Psychology, Muenzinger Hall, 345 UCB, Boulder, CO, 80309.

Abstract

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The classical twin design uses data on the variation of and covariation between monozygotic and dizygotic twins to infer underlying genetic and environmental causes of phenotypic variation in the population. By using data from additional relative classes, such as parents, extended twin family designs more comprehensively describe the causes of phenotypic variation. This article introduces an extension of previous extended twin family models, the Cascade model, which uses information on twins as well as their siblings, spouses, parents, and children to differentiate two genetic and six environmental sources of phenotypic variation. The Cascade also relaxes assumptions regarding mating and cultural transmission that existed in previous extended twin family designs. The estimation of additional parameters and relaxation of assumptions is potentially important, not only because it allows more fine-grained descriptions of the causes of phenotypic variation, but more importantly, because it can reduce the biases in parameter estimates that exist in earlier designs.

Type
Articles
Copyright
Copyright © Cambridge University Press 2009