The main goal of this chapter is to describe the research designs and statistical methods that are in popular use in behavioral genetics (BG). We begin with a brief overview of the historical background to BG in general and twin studies in particular. Next, we describe some elementary statistics required for understanding biometrical modeling. Then follows a statistical model for genetic variation, as articulated by Fisher in his classic 1918 paper, in which additive and dominance genetic variance terms are defined. The coefficients of resemblance between relatives derived from this model are then implemented in structural equation models for the analysis of data from twins and other relatives. Overall the intent is to provide a general and extensible infrastructure for the modeling of genetically informative data.
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Neale, M.C. (2009). Biometrical Models in Behavioral Genetics. In: Kim, YK. (eds) Handbook of Behavior Genetics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-76727-7_2
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