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A Note on the Statistical Power in Extended Twin Designs
Open accessAbstract
The power to detect sources of genetic and environmental variance varies with sample size, study design, effect size and the statistical significance level chosen. We explored whether the power of the classical twin study may be increased by adding non-twin siblings to the classical twin design. Sample sizes to detect genetic and shared environmental variation were compared for kinships with only twins, kinships consisting of twins and one additional sibling, and kinships with twins and two additional siblings. The effect of adding siblings to the classical twin design was considered for univariate and bivariate analyses. For the univariate case, adding one non-twin sibling resulted in a decrease in sample size needed to detect additive genetic influences in the presence of environmental influences. However, adding two additional siblings did not decrease the number of subjects as compared to the classical twin design. The sample size required to detect common environmental factors was also greatly decreased by adding one non-twin sibling. Adding two non-twin siblings resulted in a small additional decrease. In models including additive genetic, dominant genetic, and unique environmental effects, adding one sibling to a twin family decreased the required sample size to detect dominant genetic influences. Adding two siblings to a twin family resulted in only a slight additional decrease in sample size. In the bivariate case a similar pattern of results was found, in addition to the observation that the overall required sample size, as expected, was lower than in the univariate case. The decrease in sample size from bivariate testing was more pronounced in a design with one or two additional siblings, as compared to a design with twins only. It is concluded that a well considered choice of family design, i.e. including families with twins and one or two additional siblings increases the statistical power to detect sources of variance due to additive and non-additive genetic influences, and common environment.
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“The absence of significant findings for non-additive genetic or shared environmental effect by no means indicates the absence of these effect, since it could also reflect a lack of power to detect these variance components (Posthuma and Boomsma 2000).”
From Genetics of Wellbeing and Its Components Satisfaction with Life, Happiness, and Quality of Life: A Review and Meta-analysis of Heritability Studies (2015) · cites this paper as Posthuma and Boomsma 2000
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Metadata
- Authors
- Posthuma, D., & Boomsma, D. I.
- Affiliations
- Vrije Universiteit Amsterdam (NL)
- ORCID
- Boomsma, Dorret I.
- Venue
- Behavior Genetics
- Published
- 2000-03
- Volume
- 30
- Issue
- 2
- Pages
- 147-158
- ISSN
- 0001-8244 (ISSN-L)
- 1573-3297
- OpenAlex
- W2149470824
- Cited by
- 272
- References
- 20
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 5 · 2023: 5 · 2022: 7 · 2021: 9 · 2020: 15 · 2019: 11 · 2018: 10 · 2017: 10 · 2016: 11 · 2015: 17 · 2014: 9 · 2013: 15 · 2012: 11
- FWCI
- 4.09
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Behavior Genetics (publishedVersion)
- PubMed (publishedVersion)
- Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
- VU Research Portal (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Assisted Reproductive Technology and Twin Pregnancy
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Keywords
- statistical power, sample size, additive genetic effects, common environmental effects, unique environmental effects, dominant genetic effects, bivariate analysis
- MeSH terms
- Analysis of Variance, Humans, Mathematical Computing, Models, Genetic, Phenotype, Social Environment, Twins, Dizygotic, Twins, Monozygotic, Genetic Variation, Twin Studies as Topic, Quantitative Trait, Heritable
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