Are Extended Twin Family Designs Worth the Trouble? A Comparison of the Bias, Precision, and Accuracy of Parameters Estimated in Four Twin Family Models

• DOI: 10.1007/s10519-009-9320-x
• Publication Date: 2009-12-15T04:49:44Z
• Authors: Matthew C. Keller; Sarah E. Medland; Laramie E. Duncan
• Keywords: Male; 0301 basic medicine; 2716 Genetics (clinical); Evolution; Parameter indeterminacy; 310; 1105 Ecology; 03 medical and health sciences; Behavior and Systematics; 1311 Genetics; Bias; Twins, Dizygotic; Humans; Computer Simulation; Family; Classical twin design; Family Health; Models, Statistical; Models, Genetic; Genetic Variation; Reproducibility of Results; Extended twin family design; Twins, Monozygotic; Model misspecification; Phenotype; Research Design; Behavior genetics; Female

The classical twin design (CTD) uses observed covariances from monozygotic and dizygotic twin pairs to infer the relative magnitudes of genetic and environmental causes of phenotypic variation. Despite its wide use, it is well known that the CTD can produce biased estimates if its stringent assumptions are not met. By modeling observed covariances of twins' relatives in addition to twins themselves, extended twin family designs (ETFDs) require less stringent assumptions, can estimate many more parameters of interest, and should produce less biased estimates than the CTD. However, ETFDs are more complicated to use and interpret, and by attempting to estimate a large number of parameters, the precision of parameter estimates may suffer. This paper is a formal investigation into a simple question: Is it worthwhile to use more complex models such as ETFDs in behavioral genetics? In particular, we compare the bias, precision, and accuracy of estimates from the CTD and three increasingly complex ETFDs. We find the CTD does a decent job of estimating broad sense heritability, but CTD estimates of shared environmental effects and the relative importance of additive versus non-additive genetic variance can be biased, sometimes wildly so. Increasingly complex ETFDs, on the other hand, are more accurate and less sensitive to assumptions than simpler models. We conclude that researchers interested in characterizing the environment or the makeup of genetic variation should use ETFDs when possible.