在放射学研究文章中声明的统计支持水平的方法审查
Amisha Pradhan1, Tom Parry1, Sue Mallett1
1Centre for Medical Imaging, University College London UCL, 5 University St, ., London, United Kingdom.
The British journal of radiology
|February 3, 2026
概括
放射学研究人员可能低估了统计学复杂性,大约四分之一的研究声称没有复杂的方法,但使用它们. 这可能会导致不适当的分析和有缺陷的结果.
科学领域:
- 放射学 放射学是一门学科.
- 医学统计 医学统计
- 研究方法研究方法研究方法学
背景情况:
- 评估放射学研究的统计支持需求对于确保分析严格至关重要.
- 研究人员对统计需求的自我评估与实际需求之间可能存在差异.
研究的目的:
- 评估合格的统计学家和放射学研究中的其他研究人员之间对统计援助的感知必要性的差异.
- 确定已发表的放射学研究中对统计复杂性的潜在低估.
主要方法:
- 进行了对欧洲放射学 (2024) 杂志50篇原创研究文章的审查.
- 研究的分类是基于作者关于统计支持的陈述,以及医学统计学家评估统计复杂性的说法.
- 关于研究设计,统计方法和分析的数据被提取并进行描述性分析.
主要成果:
- 大多数研究是观察性 (98%) 和回顾性 (76%),重点是使用MRI (70%) 的恶性瘤 (58%).
- 三分之二 (66%) 的研究被认为采用复杂的统计方法.
- 很大一部分 (26%) 声称不需要复杂的方法,但使用了假设测试,协议分析,准确度测量或回归模型.
结论:
- 大约25%的放射学研究文章低估了它们的统计复杂性.
- 这表明统计分析需求的潜在低估,以及一些研究人员需要专业的统计支持.
- 不适当的分析和误导性的发现可能是这种低估的结果.
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