Heritability estimates from human twin data by incorporating historical prior information
Heritability estimates from human twin data by incorporating historical prior information
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DOI：
10.2307/2533662
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发表时间：
1998-12-01
期刊：
影响因子：
1.9
通讯作者：
Williams, CJ
中科院分区：
文献类型：
--
作者：
Chen, MH;Manatunga, AK;Williams, CJ
Bayesian methods are commonly used in some analyses of human genetic data, such as segregation and linkage analyses, but they are not typically used for analyses of human twin data. In this paper we develop a scheme for a Bayesian analysis of human twin data. We develop prior elicitation schemes to incorporate historical information. We consider three prior schemes: fully informative, semi-informative and noninformative. We use Markov chain Monte Carlo sampling algorithms to facilitate Bayesian computation and provide detailed implementation schemes. We also develop model diagnostics for assessing the goodness of fit of twin models. Using a simulation study, we show that if the purpose of the study is to estimate the intraclass correlations or heritability in twin studies, then the semi-informative prior is as informative as the fully informative prior. Finally, a real data example is used to illustrate the proposed methodologies.
