Interpretation of statistical findings in randomised trials: a survey of statisticians using thematic analysis of open-ended questions.

IF 3.9 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Karla Hemming, Laura Kudrna, Sam Watson, Monica Taljaard, Sheila Greenfield, Beatriz Goulao, Richard Lilford
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引用次数: 0

Abstract

Background: Dichotomisation of statistical significance, rather than interpretation of effect sizes supported by confidence intervals, is a long-standing problem.

Methods: We distributed an online survey to clinical trial statisticians across the UK, Australia and Canada asking about their experiences, perspectives and practices with respect to interpretation of statistical findings from randomised trials. We report a descriptive analysis of the closed-ended questions and a thematic analysis of the open-ended questions.

Results: We obtained 101 responses across a broad range of career stages (24% professors; 51% senior lecturers; 22% junior statisticians) and areas of work (28% early phase trials; 44% drug trials; 38% health service trials). The majority (93%) believed that statistical findings should be interpreted by considering (minimal) clinical importance of treatment effects, but many (61%) said quantifying clinically important effect sizes was difficult, and fewer (54%) followed this approach in practice. Thematic analysis identified several barriers to forming a consensus on the statistical interpretation of the study findings, including: the dynamics within teams, lack of knowledge or difficulties in communicating that knowledge, as well as external pressures. External pressures included the pressure to publish definitive findings and statistical review which can sometimes be unhelpful but can at times be a saving grace. However, the concept of the minimally important difference was identified as a particularly poorly defined, even nebulous, construct which lies at the heart of much disagreement and confusion in the field.

Conclusion: The majority of participating statisticians believed that it is important to interpret statistical findings based on the clinically important effect size, but report this is difficult to operationalise. Reaching a consensus on the interpretation of a study is a social process involving disparate members of the research team along with editors and reviewers, as well as patients who likely have a role in the elicitation of minimally important differences.

随机试验中统计结果的解释:利用开放式问题的主题分析对统计人员进行的调查。
背景:统计显著性的二分法,而非置信区间支持的效应大小解释,是一个长期存在的问题:统计显著性的二分法,而不是在置信区间支持下解释效应大小,是一个长期存在的问题:我们向英国、澳大利亚和加拿大的临床试验统计人员发放了一份在线调查问卷,询问他们在解释随机试验统计结果方面的经验、观点和做法。我们对封闭式问题进行了描述性分析,对开放式问题进行了主题分析:我们获得了 101 份答复,这些答复涉及不同的职业阶段(24% 教授;51% 高级讲师;22% 初级统计员)和工作领域(28% 早期试验;44% 药物试验;38% 医疗服务试验)。大多数人(93%)认为,应通过考虑治疗效果的(最小)临床重要性来解释统计结果,但许多人(61%)表示,量化具有临床重要性的效应大小很困难,而在实践中采用这种方法的人数较少(54%)。专题分析发现了就研究结果的统计学解释达成共识的几个障碍,包括:团队内部的动态、缺乏知识或难以传达知识,以及外部压力。外部压力包括发表最终研究结果和统计审查的压力,这有时可能无益,但有时也是一种拯救。然而,"最小重要差异 "的概念被认为是一个定义不清、甚至模糊不清的概念,是该领域中许多分歧和混乱的核心所在:大多数参与研究的统计学家认为,根据临床重要效应大小来解释统计结果非常重要,但报告称这很难操作化。就一项研究的解释达成共识是一个社会过程,涉及到研究团队的不同成员、编辑和审稿人,以及可能在最小重要差异的激发中发挥作用的患者。
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
BMC Medical Research Methodology
BMC Medical Research Methodology 医学-卫生保健
CiteScore
6.50
自引率
2.50%
发文量
298
审稿时长
3-8 weeks
期刊介绍: BMC Medical Research Methodology is an open access journal publishing original peer-reviewed research articles in methodological approaches to healthcare research. Articles on the methodology of epidemiological research, clinical trials and meta-analysis/systematic review are particularly encouraged, as are empirical studies of the associations between choice of methodology and study outcomes. BMC Medical Research Methodology does not aim to publish articles describing scientific methods or techniques: these should be directed to the BMC journal covering the relevant biomedical subject area.
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