统计抽样验证源数据:实施中的问题

A. Grieve
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引用次数: 11

摘要

药物开发过程的效率一直是制药公司、政府、监管机构和患者关注的问题。虽然人们在遗传学和复杂的统计设计上花费了大量的时间和精力,但对控制临床试验运行的过程的关注却较少。在本文中,我描述了一种用于源数据验证的统计方法,其实现可能会对试验监视器的工作量产生很大影响。我调查了一种不太严格的源数据验证形式对数据质量的影响,以及可以从数据中得出的推论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Source Data Verification by Statistical Sampling: Issues in Implementation
Efficiency of the drug development process is a continuing concern for pharmaceutical companies, governments, regulatory authorities, and patients. While much time and effort have been spent on developments in genetics and on sophisticated statistical designs, there has been less concern about the processes that govern the running of clinical trials. In this article, I describe a statistical method for source data verification whose implementation can have a large impact on the workload of trial monitors. I investigate the consequences of a less stringent form of source data verification on the quality of data and the inferences that can be drawn from the data.
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