Behavior Genetics

, 36:331

Likelihood Ratio Tests in Behavioral Genetics: Problems and Solutions

  • Annica Dominicus
  • Anders Skrondal
  • Håkon K. Gjessing
  • Nancy L. Pedersen
  • Juni Palmgren
Article

DOI: 10.1007/s10519-005-9034-7

Cite this article as:
Dominicus, A., Skrondal, A., Gjessing, H.K. et al. Behav Genet (2006) 36: 331. doi:10.1007/s10519-005-9034-7

The likelihood ratio test of nested models for family data plays an important role in the assessment of genetic and environmental influences on the variation in traits. The test is routinely based on the assumption that the test statistic follows a chi-square distribution under the null, with the number of restricted parameters as degrees of freedom. However, tests of variance components constrained to be non-negative correspond to tests of parameters on the boundary of the parameter space. In this situation the standard test procedure provides too large p-values and the use of the Akaike Information Criterion (AIC) or the Bayesian Information Criterion (BIC) for model selection is problematic. Focusing on the classical ACE twin model for univariate traits, we adapt existing theory to show that the asymptotic distribution for the likelihood ratio statistic is a mixture of chi-square distributions, and we derive the mixing probabilities. We conclude that when testing the AE or the CE model against the ACE model, the p-values obtained from using the χ2(1 df) as the reference distribution should be halved. When the E model is tested against the ACE model, a mixture of χ2(0 df), χ2(1 df) and χ2(2 df) should be used as the reference distribution, and we provide a simple formula to compute the mixing probabilities. Similar results for tests of the AE, DE and E models against the ADE model are also derived. Failing to use the appropriate reference distribution can lead to invalid conclusions.

Keywords

Boundary parameter chi-square distribution likelihood ratio test twin model variance component 

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Annica Dominicus
    • 1
    • 2
    • 6
  • Anders Skrondal
    • 3
    • 4
  • Håkon K. Gjessing
    • 4
  • Nancy L. Pedersen
    • 2
    • 5
  • Juni Palmgren
    • 1
    • 2
  1. 1.Department of MathematicsStockholm UniversityStockholmSweden
  2. 2.Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
  3. 3.Department of StatisticsLondon School of EconomicsLondonUK
  4. 4.Division of EpidemiologyNorwegian Institute of Public HealthOsloNorway
  5. 5.Department of PsychologyUniversity of Southern CaliforniaLos AngelesUSA
  6. 6.Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden

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