Abstract
| Original language | English |
|---|---|
| Article number | 33 |
| Journal | Journal of Open Research Software |
| Volume | 5 |
| DOIs | |
| Publication status | Published - 1 Jan 2017 |
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BayesTwin : An R package for Bayesian inference of item-level twin data. / Schwabe, I.
In: Journal of Open Research Software, Vol. 5, 33, 01.01.2017.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - BayesTwin
T2 - An R package for Bayesian inference of item-level twin data
AU - Schwabe, I.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
U2 - 10.5334/jors.185
DO - 10.5334/jors.185
M3 - Article
VL - 5
JO - Journal of Open Research Software
JF - Journal of Open Research Software
SN - 2049-9647
M1 - 33
ER -