估计员
样本量测定
一致性(知识库)
计算机科学
计量经济学
统计
样品(材料)
计算
随机效应模型
协变量
数学
算法
人工智能
医学
荟萃分析
内科学
化学
色谱法
作者
Hui Quan,Xuezhou Mao,Joshua Chen,Weichung Joe Shih,Soo Peter Ouyang,Ji Zhang,Peng-Liang Zhao,Bruce Binkowitz
摘要
We can apply both fixed and random effects models to multi-regional clinical trial (MRCT) design and data analysis. Thoroughly, understanding the features of these models in an MRCT setting will help assessing their applicability to an MRCT. In this paper, we discuss the interpretations of trial results from these models. We also evaluate the impact of the number of regions and the sample size configuration across the regions on the required total sample size for the overall treatment effect assessment. For quantifying treatment effects of individual regions, the empirical shrinkage estimator and the James-Stein type shrinkage estimator associate with smaller variability compared with the regular sample estimator. We conduct computation and simulation to compare the performance of these estimators when they are applied to assess consistency of treatment effects across regions. We use a multinational trial example to illustrate the application of these methods.
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