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随机成本效益分析的功效与样本量计算。

Power and sample size calculations for stochastic cost-effectiveness analysis.

作者信息

Briggs A H, Gray A M

机构信息

University of Oxford, Health Economics Research Centre, Institute of Health Sciences, Headington, United Kingdom.

出版信息

Med Decis Making. 1998 Apr-Jun;18(2 Suppl):S81-92. doi: 10.1177/0272989X98018002S10.

Abstract

As the data for economic analyses are increasingly collected prospectively alongside clinical trials, many commentators have highlighted that the sample sizes in such trials should be based on the requirements for the economic analysis as well as those for the clinical evaluation. However, issues associated with sample size calculations for economic analysis have yet to receive the rigorous attention given to sample size calculation for clinical evaluation. In particular, no sample size formula for cost-effectiveness analysis is available for analysts hoping either to calculate the required sample size at the design stage of a study or to calculate the power a given size of clinical trial will generate for cost-effectiveness analysis. Building on the recent literature for calculating confidence intervals for cost-effectiveness ratios, the authors explore possible techniques for deriving a sample size formula for cost-effectiveness analysis based on simple combination of the confidence limits on costs and effects.

摘要

随着经济分析数据越来越多地在临床试验期间前瞻性收集,许多评论者强调,此类试验的样本量应基于经济分析以及临床评估的要求。然而,与经济分析样本量计算相关的问题尚未得到像临床评估样本量计算那样的严格关注。特别是,对于希望在研究设计阶段计算所需样本量或计算给定规模的临床试验对成本效益分析将产生的检验效能的分析人员而言,尚无用于成本效益分析的样本量公式。基于近期有关计算成本效益比置信区间的文献,作者探索了基于成本和效果置信限的简单组合来推导成本效益分析样本量公式的可能技术。

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