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Assessing Genotype by Environment Interaction in Case of Heterogeneous Measurement Error

Behavior Genetics volume 44, pages 394–406 (2014)Cite this article

Abstract

Considerable effort has been devoted to establish genotype by environment interaction (G \(\times \) E) in case of unmeasured genetic and environmental influences. Although it has been outlined by various authors that the appearance of G \(\times \) E can be dependent on properties of the given measurement scale, a non-biased method to assess G \(\times \) E is still lacking. We show that the incorporation of an explicit measurement model can remedy potential bias due to ceiling and floor effects. By means of a simulation study it is shown that the use of sum scores can lead to biased estimates whereas the proposed method is unbiased. The power of the suggested method is illustrated by means of a second simulation study with different sample sizes and G \(\times \) E effect sizes.

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Acknowledgments

This study was funded by the PROO Grant 411-12-623 from the Netherlands Organisation for Scientific Research (NWO).

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

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Authors and Affiliations

  1. Department of Research Methodology, Measurement, and Data Analysis, University of Twente, Drienerlolaan 5, 7522 NB,  Enschede, The Netherlands

    Inga Schwabe & Stéphanie M. van den Berg

Authors
  1. Inga Schwabe
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  2. Stéphanie M. van den Berg
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Correspondence to Inga Schwabe.

Additional information

Edited by Gitta Lubke.

Appendix 1: JAGS script

Appendix 1: JAGS script

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Schwabe, I., van den Berg, S.M. Assessing Genotype by Environment Interaction in Case of Heterogeneous Measurement Error. Behav Genet 44, 394–406 (2014). https://doi.org/10.1007/s10519-014-9649-7

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Keywords

  • Genotype by environment interaction
  • Heterogeneous measurement error
  • Item response theory
  • Sum scores
  • Twin studies