ArticleBehavior genetics2021
Multilevel Twin Models: Geographical Region as a Third Level Variable.
Article in Behavior genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Tracing the Right Path: Determination of Large Pedigree Segmentation and Relatedness.Behavior genetics · 2026Article
- The Power to Resolve Cultural Transmission and Sibling Interaction Using Polygenic Scores.Behavior genetics · 2026Article
- Does neighbourhood deprivation influence low back pain and arthritis: An empirical study using multilevel twin design.PloS one · 2024Article
- Worldwide Well-Being: Simulated Twins Reveal Genetic and (Hidden) Environmental Influences.Perspectives on psychological science : a journal of the Association for Psychological Science · 2023Article
- Maximizing the value of twin studies in health and behaviour.Nature human behaviour · 2023Review
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Authors and funding
10 authors.
Funding
Abstract
The classical twin model can be reparametrized as an equivalent multilevel model. The multilevel parameterization has underexplored advantages, such as the possibility to include higher-level clustering variables in which lower levels are nested. When this higher-level clustering is not modeled, its variance is captured by the common environmental variance component. In this paper we illustrate the application of a 3-level multilevel model to twin data by analyzing the regional clustering of 7-year-old children's height in the Netherlands. Our findings show that 1.8%, of the phenotypic variance in children's height is attributable to regional clustering, which is 7% of the variance explained by between-family or common environmental components. Since regional clustering may represent ancestry, we also investigate the effect of region after correcting for genetic principal components, in a subsample of participants with genome-wide SNP data. After correction, region no longer explained variation in height. Our results suggest that the phenotypic variance explained by region might represent ancestry effects on height.
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Registered trials
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