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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

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DF-analyses of heritability with double-entry twin data: asymptotic standard errors and efficient estimation.

H P Kohler¹, J L Rodgers

¹Head of Research Group on Social Dynamics and Fertility, Max Planck Institute for Demographic Research, Rostock, Germany. kohler@demogr.mpg.de

Behavior Genetics

|September 8, 2001

Summary

This study details the asymptotic distribution for DeFries Fulker (DF) regression estimates in twin studies. The findings enhance statistical power for analyzing heritability and environmental influences using twin data.

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Area of Science:

Quantitative genetics
Behavioral genetics
Statistical genetics

Background:

DeFries Fulker (DF) regression is a key method for estimating genetic and environmental influences in twin studies.
Accurate estimation of heritability and shared environmental influences requires robust statistical methods.
Previous DF-regression analyses may lack sufficient statistical power for detecting effects.

Purpose of the Study:

To establish the asymptotic distribution of DeFries Fulker (1985) regression estimates for heritability and shared environmental influences using double-entry twin data.
To provide a method for increasing statistical power in twin analyses.
To introduce an efficient DF-analysis for improved precision with additional covariates.

Main Methods:

Derivation of the asymptotic distribution for DF-regression coefficients.
Development of a formula for estimating the covariance matrix of DF-regression coefficients.
Application of the method to simulated and real-world Danish twin data.

Main Results:

The asymptotic distribution of DF-regression estimates is established for double-entry twin data.
A simple formula for the covariance matrix of DF-regression coefficients is provided.
The proposed method significantly increases statistical power in twin analyses.
An 'efficient DF-analysis' offers more precise estimates when incorporating additional covariates.

Conclusions:

The established asymptotic distribution provides a theoretical foundation for DF-regression in twin studies.
The developed methods enhance the statistical power and precision of heritability and environmental influence estimates.
This approach offers a valuable tool for researchers in behavioral and quantitative genetics.