Statistical evaluation of learning curve effects in surgical trials.
Statistical evaluation of learning curve effects in surgical trials.
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DOI：
10.1191/1740774504cn042oa
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发表时间：
2004-01-01
期刊：
影响因子：
--
通讯作者：
Fayers, Peter
中科院分区：
文献类型：
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作者：
Cook, Jonathan A;Ramsay, Craig R;Fayers, Peter
外科手术中的随机对照试验（RCT）一直受到新技术技术性能随时间推移（“学习曲线”）可能扭曲比较的担忧的阻碍。试验中学习曲线的统计评估很少受到关注。本文讨论了什么是学习曲线效应，影响学习曲线效应的因素，如何显示学习曲线效应，以及如何将学习曲线效应纳入试验分析。贝叶斯分层模型提出了调整的学习曲线效应的存在的试验结果。试验评价和数据收集的影响被认为是。
Randomized controlled trials (RCTs) in surgery have been impeded by concerns that improvements in the technical performance of a new technique over time (a "learning curve") may distort comparisons. The statistical assessment of learning curves in trials has received little attention. In this paper, we discuss what a learning curve effect is, the factors which effect it, how to display it, and how to incorporate the learning effect into the trial analysis. Bayesian hierarchical models are proposed to adjust the trial results for the existence of a learning curve effect. The implications for trial evaluation and data collection are considered.