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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Veröffentlicht in:Journal of open research software Jg. 5; H. 1; S. 33
1. Verfasser: Schwabe, Inga
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Ubiquity Press Ltd 14.11.2017
Ubiquity Press
Schlagworte:
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
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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
ISSN:2049-9647
2049-9647
DOI:10.5334/jors.185