Bayesian statistics in genetics - a guide for the uninitiated

被引:103
作者
Shoemaker, JS
Painter, IS
Weir, BS
机构
[1] Duke Univ, Med Ctr, Control Res Program, Durham, NC 27710 USA
[2] Talaria Inc, Seattle, WA 98104 USA
[3] N Carolina State Univ, Dept Stat, Raleigh, NC 27695 USA
关键词
D O I
10.1016/S0168-9525(99)01751-5
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Statistical analyses are used in many fields of genetic research. Most geneticists are taught classical statistics, which includes hypothesis testing, estimation and the construction of confidence intervals; this framework has proved more than satisfactory in many ways. What does a Bayesian framework have to offer geneticists? Its utility lies in offering a more direct approach to some questions and the incorporation of prior information. It can also provide a more straightforward interpretation of results. The utility of a Bayesian perspective, especially for complex problems, is becoming increasingly clear to the statistics community; geneticists are also finding this framework useful and are increasingly utilizing the power of this approach.
引用
收藏
页码:354 / 358
页数:5
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