Tikaradze E, Sharashenidze G, Sanikidze T, Jafaridze S, Ormotsadze G
Tbilisi State Medical University; Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia.
Georgian Med News. 2020 Mar(300):124-128.
Bayesian approach for the sample size determination (SSD) and a comparison with classical (Frequentist) approach are presented. Credible interval length estimation-type criterion was applied for the Bayesian SSD estimation in population studies of cytogenetic characteristics. The dependence of the sample size (n) on the length of the 95% Credible interval of the population mean has been estimated in the Gaussian approximation of the distribution functions with known variance and an unknown population mean. The Mean and Variance of the prior function in the Bayesian approach were estimated based on published data and the results of our previous studies. Mathematical analysis and graphical visualization of the results was carried out using the software STATISTICA-12, and WinBugs. It is shown that the Bayesian approach achieves an almost two-fold decrease in sample size and provides the possibility of flexible optimization of the planned procedures at the preliminary stage of the study. Further increase inaccuracy of the results is expected due to a more accurate approximation of asymmetric distributions using gamma functions.
本文介绍了用于样本量确定(SSD)的贝叶斯方法以及与经典(频率论)方法的比较。在细胞遗传学特征的群体研究中,可信区间长度估计型标准被应用于贝叶斯SSD估计。在分布函数的高斯近似中,已知方差且总体均值未知,估计了样本量(n)对总体均值95%可信区间长度的依赖性。贝叶斯方法中先验函数的均值和方差是根据已发表的数据和我们之前研究的结果估计的。使用STATISTICA - 12软件和WinBugs对结果进行了数学分析和图形可视化。结果表明,贝叶斯方法使样本量几乎减少了一半,并在研究的初步阶段提供了灵活优化计划程序的可能性。由于使用伽马函数对非对称分布进行了更精确的近似,预计结果的不准确性会进一步增加。