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两阶段临床试验中响应比例的均方误差降低估计量。

An MSE-reduced estimator for the response proportion in a two-stage clinical trial.

作者信息

Li Qizhai

机构信息

Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, CAS, Zhongguancun, Beijing, China.

出版信息

Pharm Stat. 2011 May-Jun;10(3):277-9. doi: 10.1002/pst.414. Epub 2010 Feb 5.

Abstract

Two-stage design is very useful in clinical trials for evaluating the validity of a specific treatment regimen. When the second stage is allowed to continue, the method used to estimate the response rate based on the results of both stages is critical for the subsequent design. The often-used sample proportion has an evident upward bias. However, the maximum likelihood estimator or the moment estimator tends to underestimate the response rate. A mean-square error weighted estimator is considered here; its performance is thoroughly investigated via Simon's optimal and minimax designs and Shuster's design. Compared with the sample proportion, the proposed method has a smaller bias, and compared with the maximum likelihood estimator, the proposed method has a smaller mean-square error.

摘要

两阶段设计在评估特定治疗方案有效性的临床试验中非常有用。当允许第二阶段继续进行时,基于两个阶段的结果来估计缓解率所使用的方法对于后续设计至关重要。常用的样本比例存在明显的向上偏差。然而,最大似然估计器或矩估计器往往会低估缓解率。本文考虑了一种均方误差加权估计器;通过西蒙的最优和极小极大设计以及舒斯特的设计对其性能进行了全面研究。与样本比例相比,所提出的方法偏差较小,与最大似然估计器相比,所提出的方法均方误差较小。

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