Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction. (6th November 2017)
- Record Type:
- Journal Article
- Title:
- Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction. (6th November 2017)
- Main Title:
- Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction
- Authors:
- Schwabe, Inga
Boomsma, Dorret I.
van den Berg, Stéphanie M. - Abstract:
- Abstract : Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2, 110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences inAbstract : Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2, 110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES. … (more)
- Is Part Of:
- Twin research and human genetics. Volume 20:Number 6(2017)
- Journal:
- Twin research and human genetics
- Issue:
- Volume 20:Number 6(2017)
- Issue Display:
- Volume 20, Issue 6 (2017)
- Year:
- 2017
- Volume:
- 20
- Issue:
- 6
- Issue Sort Value:
- 2017-0020-0006-0000
- Page Start:
- 511
- Page End:
- 520
- Publication Date:
- 2017-11-06
- Subjects:
- mathematical ability, -- SES, -- IRT, -- genotype by environment interaction
Twins -- Periodicals
Multiple birth -- Periodicals
618.25 - Journal URLs:
- http://journals.cambridge.org/action/displayBackIssues?jid=THG ↗
http://journals.cambridge.org/action/displayJournal?jid=THG ↗
http://www.ingentaconnect.com/content/aap/twg ↗ - DOI:
- 10.1017/thg.2017.59 ↗
- Languages:
- English
- ISSNs:
- 1832-4274
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 5257.xml