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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Using bivariate models to understand between- and within-cluster regression coefficients, with application to twin

Lyle C Gurrin1, John B Carlin, Jonathan A C Sterne

  • 1Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, University of Melbourne, Carlton, Victoria 3053, Australia. lgurrin@unimelb.edu.au

Biometrics
|September 21, 2006
PubMed
Summary

Comparing regression effects in monozygous (MZ) and dizygous (DZ) twins is proposed to identify genetic origins of exposure-outcome associations. However, genetic correlations in twin pairs do not always lead to distinct MZ and DZ within-pair regression effects.

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Area of Science:

  • Biostatistics
  • Twin Studies
  • Genetic Epidemiology

Background:

  • Regression analysis of clustered data requires distinct between- and within-cluster exposure effects.
  • Within-pair regression in twin data assesses associations conditional on shared genetic or environmental factors.
  • Comparing monozygous (MZ) and dizygous (DZ) twin regression effects is a proposed method to infer genetic origins of associations.

Purpose of the Study:

  • To propose a bivariate model for analyzing exposure and outcome in twin-pair data.
  • To investigate conditions under which within-pair regression effects differ between MZ and DZ twins.
  • To examine if apparent genetic correlations in twin data necessarily translate to distinct MZ and DZ within-pair regression coefficients.

Main Methods:

  • Development of a bivariate regression model for twin-pair exposure and outcome data.
  • Derivation of between- and within-pair regression coefficients as weighted averages of variance and covariance ratios.
  • Analysis of conditions influencing the distinction between MZ and DZ within-pair regression effects.

Main Results:

  • Within-pair regression coefficients are shown to be functions of exposure and outcome variances and covariances.
  • Conditions are identified for when MZ and DZ within-pair regression effects will differ.
  • A genetic correlation structure between exposure and outcome in twin pairs does not guarantee distinct MZ and DZ within-pair regression coefficients.

Conclusions:

  • The proposed bivariate model provides a framework for analyzing twin data with distinct between- and within-pair effects.
  • Apparent genetic influences on exposure-outcome associations in twin studies may not always be reflected in differing MZ and DZ within-pair regression coefficients.
  • The study highlights the importance of carefully interpreting within-pair regression effects in twin studies when inferring genetic origins.