BayesTwin: An R Package for Bayesian Inference of Item-Level Twin Data

BayesTwin is an open-source R package that serves as a pipeline to the MCMC program JAGS to perform Bayesian inference on genetically-informative hierarchical twin data. Simultaneously to the biometric model, an item response theory (IRT) measurement model is estimated, allowing analysis of the raw...

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Vydáno v:Journal of open research software Ročník 5; číslo 1; s. 33
Hlavní autor: Schwabe, Inga
Médium: Journal Article
Jazyk:angličtina
Vydáno: Ubiquity Press Ltd 14.11.2017
Ubiquity Press
Témata:
Applied research
Bayesian inference
Data processing
Genetics
Genotype-environment interaction
Heritability
Item response theory
Measurement error
Methods
R (Programming language)
Software engineering
Software package
Twin data
ISSN:2049-9647, 2049-9647
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Abstract BayesTwin is an open-source R package that serves as a pipeline to the MCMC program JAGS to perform Bayesian inference on genetically-informative hierarchical twin data. Simultaneously to the biometric model, an item response theory (IRT) measurement model is estimated, allowing analysis of the raw phenotypic (item-level) data. The integration of such a measurement model is important since earlier research has shown that an analysis based on an aggregated measure (e.g., a sum-score based analysis) can lead to an underestimation of heritability and the spurious finding of genotype-environment interactions. The package includes all common biometric and IRT models as well as functions that help plot relevant information or determine whether the analysis was performed well. Keywords: Heritability, Bayesian inference, Twin data, Genetics, Item response theory, Measurement error, Genotype-environment interaction, R, Software package
AbstractList BayesTwin is an open-source R package that serves as a pipeline to the MCMC program JAGS to perform Bayesian inference on genetically-informative hierarchical twin data. Simultaneously to the biometric model, an item response theory (IRT) measurement model is estimated, allowing analysis of the raw phenotypic (item-level) data. The integration of such a measurement model is important since earlier research has shown that an analysis based on an aggregated measure (e.g., a sum-score based analysis) can lead to an underestimation of heritability and the spurious finding of genotype-environment interactions. The package includes all common biometric and IRT models as well as functions that help plot relevant information or determine whether the analysis was performed well. Keywords: Heritability, Bayesian inference, Twin data, Genetics, Item response theory, Measurement error, Genotype-environment interaction, R, Software package
BayesTwin is an open-source R package that serves as a pipeline to the MCMC program JAGS to perform Bayesian inference on genetically-informative hierarchical twin data. Simultaneously to the biometric model, an item response theory (IRT) measurement model is estimated, allowing analysis of the raw phenotypic (item-level) data. The integration of such a measurement model is important since earlier research has shown that an analysis based on an aggregated measure (e.g., a sum-score based analysis) can lead to an underestimation of heritability and the spurious finding of genotype-environment interactions. The package includes all common biometric and IRT models as well as functions that help plot relevant information or determine whether the analysis was performed well. Funding statement: Partly funded by the PROO grant 411-12-623 from the Netherlands Organisation for Scientific Research (NWO).
BayesTwin is an open-source R package that serves as a pipeline to the MCMC program JAGS to perform Bayesian inference on genetically-informative hierarchical twin data. Simultaneously to the biometric model, an item response theory (IRT) measurement model is estimated, allowing analysis of the raw phenotypic (item-level) data. The integration of such a measurement model is important since earlier research has shown that an analysis based on an aggregated measure (e.g., a sum-score based analysis) can lead to an underestimation of heritability and the spurious finding of genotype-environment interactions. The package includes all common biometric and IRT models as well as functions that help plot relevant information or determine whether the analysis was performed well.
Audience Academic
Author Schwabe, Inga
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crossref_primary_10_1093_ve_vead015
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crossref_primary_10_1007_s10519_023_10168_5
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SubjectTerms Applied research
Bayesian inference
Data processing
Genetics
Genotype-environment interaction
Heritability
Item response theory
Measurement error
Methods
R (Programming language)
Software engineering
Software package
Twin data
Title BayesTwin: An R Package for Bayesian Inference of Item-Level Twin Data
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