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Updated: Jul 11, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
确定与风险相称的方法来验证临床试验的统计编程
Carrol Gamble1, Steff Lewis2, Deborah Stocken3
1Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK.
统计编程验证对于临床试验完整性至关重要. 一种基于风险的新方法确保了试验数据分析的科学准确性和有效的资源使用.
科学领域:
- 临床试验 临床试验
- 统计编程 统计编程
- 监管合规性 监管合规性
背景情况:
- 统计学家在临床试验中的作用对于设计和分析至关重要.
- 结果的可复制性取决于严格的文档和统计程序的验证.
- 现有的软件验证指南没有充分解决由统计学家编写的程序.
结论:
- 开发了一种基于风险的新方法来验证统计编程.
- 这种方法旨在有效地实施有针对性的质量保证.
- 它支持科学完整性,并优化临床试验单位的资源配置.
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