使用贝叶斯方法估计相关系数及其在流行病学研究中的应用。
Estimation of the correlation coefficient using the Bayesian Approach and its applications for epidemiologic research.
作者信息
Schisterman Enrique F, Moysich Kirsten B, England Lucinda J, Rao Malla
机构信息
Division of Epidemiology, Statistics and Prevention National Institute of Child Health and Human Development/National Institute of Health, Bethesda, MD, USA.
出版信息
BMC Med Res Methodol. 2003 Mar 25;3:5. doi: 10.1186/1471-2288-3-5.
BACKGROUND
The Bayesian approach is one alternative for estimating correlation coefficients in which knowledge from previous studies is incorporated to improve estimation. The purpose of this paper is to illustrate the utility of the Bayesian approach for estimating correlations using prior knowledge.
METHODS
The use of the hyperbolic tangent transformation (rho = tanh xi and r = tanh z) enables the investigator to take advantage of the conjugate properties of the normal distribution, which are expressed by combining correlation coefficients from different studies.
CONCLUSIONS
One of the strengths of the proposed method is that the calculations are simple but the accuracy is maintained. Like meta-analysis, it can be seen as a method to combine different correlations from different studies.
背景
贝叶斯方法是估计相关系数的一种替代方法，该方法纳入了先前研究的知识以改进估计。本文的目的是说明使用先验知识的贝叶斯方法在估计相关性方面的效用。
方法
使用双曲正切变换（ρ = tanh ξ 且 r = tanh z）使研究者能够利用正态分布的共轭性质，这些性质通过合并来自不同研究的相关系数来体现。
结论
所提出方法的优点之一是计算简单但精度得以保持。与荟萃分析一样，它可被视为一种合并来自不同研究的不同相关性的方法。
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