Assessing Genotype by Environment Interaction in Case of Heterogeneous Measurement Error

I. Schwabe, Stéphanie M. Van Den Berg

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Considerable effort has been devoted to establish genotype by environment interaction (GxE) in case of unmeasured genetic and environmental influences. Although it has been outlined by various authors that the appearance of G E can be dependent on properties of the given measurement scale, a non-biased method to assess GxE 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 GxE effect sizes.
Original languageEnglish
JournalBehavior Genetics
DOIs
Publication statusPublished - 2014
Externally publishedYes

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title = "Assessing Genotype by Environment Interaction in Case of Heterogeneous Measurement Error",
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Assessing Genotype by Environment Interaction in Case of Heterogeneous Measurement Error. / Schwabe, I.; Van Den Berg, Stéphanie M.

In: Behavior Genetics, 2014.

Research output: Contribution to journalArticleScientificpeer-review

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AB - Considerable effort has been devoted to establish genotype by environment interaction (GxE) in case of unmeasured genetic and environmental influences. Although it has been outlined by various authors that the appearance of G E can be dependent on properties of the given measurement scale, a non-biased method to assess GxE 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 GxE effect sizes.

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