Comments on ‘standard and reference‐based conditional mean imputation’: Regulators and trial statisticians be aware!

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Suzie Cro, Tim P. Morris, James H. Roger, James R. Carpenter
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引用次数: 0

Abstract

Accurate frequentist performance of a method is desirable in confirmatory clinical trials, but is not sufficient on its own to justify the use of a missing data method. Reference‐based conditional mean imputation, with variance estimation justified solely by its frequentist performance, has the surprising and undesirable property that the estimated variance becomes smaller the greater the number of missing observations; as explained under jump‐to‐reference it effectively forces the true treatment effect to be exactly zero for patients with missing data.
关于 "基于标准和参照的条件均值估算 "的评论:监管者和试验统计人员须知!
在确证性临床试验中,一种方法的精确频数性能是可取的,但其本身并不足以证明使用缺失数据方法是合理的。基于参照的条件均值估算法的方差估计仅以其频数性能为依据,但却有一个令人惊讶且不可取的特性,即缺失观察指标越多,估计方差越小;正如 "跳至参照 "所解释的那样,它实际上迫使缺失数据患者的真实治疗效果恰好为零。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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