Multilevel Modeling in Classical Twin and Modern Molecular Behavior Genetics.

Area of Science:

• Behavioral Genetics
• Quantitative Genetics
• Multilevel Modeling

Background:

• Behavior genetics models for single phenotypes are often estimated using multilevel models.
• Existing methods have limitations in generalizing to multiple phenotypes and complex nesting structures.

Purpose of the Study:

• To extend behavior genetics models to accommodate multiple phenotypes within a general multilevel framework.
• To incorporate higher and lower levels of nesting, including child, family, and neighborhood contexts.
• To provide a unified approach that merges with molecular genetics analyses.

Main Methods:

• Utilizing a multivariate three-level multilevel model.
• Accounting for variation at the child (unique environment, additive genetics), family (additive genetics, common environment), and neighborhood (broader contexts) levels.
• Providing R functions and code for implementing these models using OpenMx.

Main Results:

• Demonstrated the generalizability of multilevel modeling to complex behavior genetics research.
• Successfully fitted a multivariate three-level model incorporating genetic and environmental factors at multiple nested levels.
• Developed practical computational tools for applying these advanced models.

Conclusions:

• Multilevel modeling offers a flexible and comprehensive framework for behavior genetics research involving multiple phenotypes and nested structures.
• The extended method integrates traditional behavior genetics with molecular genetics approaches.
• The provided R code facilitates the application of these advanced statistical techniques.