Behavior Genetics

, Volume 39, Issue 2, pp 220–229

A Note on the Parameterization of Purcell’s G × E Model for Ordinal and Binary Data

  • Sarah E. Medland
  • Michael C. Neale
  • Lindon J. Eaves
  • Benjamin M. Neale
BRIEF COMMUNICATION

DOI: 10.1007/s10519-008-9247-7

Cite this article as:
Medland, S.E., Neale, M.C., Eaves, L.J. et al. Behav Genet (2009) 39: 220. doi:10.1007/s10519-008-9247-7

Abstract

Following the publication of Purcell’s approach to the modeling of gene by environment interaction in 2002, the interest in G × E modeling in twin and family data increased dramatically. The analytic techniques described by Purcell were designed for use with continuous data. Here we explore the re-parameterization of these models for use with ordinal and binary outcome data. Analysis of binary and ordinal data within the context of a liability threshold model traditionally requires constraining the total variance to unity to ensure identification. Here, we demonstrate an alternative approach for use with ordinal data, in which the values of the first two thresholds are fixed, thus allowing the total variance to change as function of the moderator. We also demonstrate that when using binary data, constraining the total variance to unity for a given value of the moderator is sufficient to ensure identification. Simulation results indicate that analyses of ordinal and binary data can recover both the raw and standardized patterns of results. However, the scale of the results is dependent on the specification of (threshold or variance) constraints rather than the underlying distribution of liability. Example Mx scripts are provided.

Keywords

Genotype by environment interaction Structural equation model Twin data Ordinal data G × E 

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Sarah E. Medland
    • 1
    • 2
  • Michael C. Neale
    • 2
    • 3
    • 4
    • 5
  • Lindon J. Eaves
    • 2
    • 3
    • 4
  • Benjamin M. Neale
    • 6
    • 7
    • 8
  1. 1.Genetic Epidemiology UnitQueensland Institute of Medical ResearchBrisbaneAustralia
  2. 2.Virginia Institute of Psychiatric and Behavioral GeneticsVirginia Commonwealth UniversityRichmondVAUSA
  3. 3.Department of PsychiatryVirginia Commonwealth UniversityRichmondUSA
  4. 4.Department of Human GeneticsVirginia Commonwealth UniversityRichmondUSA
  5. 5.Department of Biological PsychologyFree UniversityAmsterdamThe Netherlands
  6. 6.Social, Genetic, and Developmental Psychiatry CentreInstitute of Psychiatry, King’s CollegeLondonUK
  7. 7.Broad Institute of MIT and Harvard UniversityCambridgeUSA
  8. 8.Center for Human Genetic Research, Massachusetts General HospitalHarvard Medical SchoolBostonUSA

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