Does bad inference drive out good?
Does bad inference drive out good?
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DOI：
10.1111/1440-1681.12422
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发表时间：
2015-07-01
影响因子：
2.9
通讯作者：
Marozzi, Marco
中科院分区：
文献类型：
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作者：
Marozzi, Marco
统计数据在实践中的（错误）使用引起了广泛的辩论，其中一个辩论特别活跃的领域是医学。许多学者强调，很大一部分已发表的医学研究包含统计错误。人们注意到，像《自然医学》和《新英格兰医学杂志》这样的顶级期刊发表的论文中有相当大的比例包含统计错误，并且对统计方法的应用记录不佳。本文加入了关于医学文献中统计学（错误）使用的辩论。尽管统计结果的验证过程可能相当难以捉摸，但对基本假设的仔细评估在医学以及其他应用统计方法的领域中至关重要。不幸的是，许多论文（包括发表在顶级期刊上的论文）都没有对潜在假设进行仔细评估。在本文中，它表明，非参数方法是很好的替代参数方法时，后者的假设不满足。解决医学文献中统计学误用问题的一个关键点是所有期刊都有自己的统计学家来审查每篇投稿论文中的统计方法/分析部分。
The (mis)use of statistics in practice is widely debated, and a field where the debate is particularly active is medicine. Many scholars emphasize that a large proportion of published medical research contains statistical errors. It has been noted that top class journals like Nature Medicine and The New England Journal of Medicine publish a considerable proportion of papers that contain statistical errors and poorly document the application of statistical methods. This paper joins the debate on the (mis)use of statistics in the medical literature. Even though the validation process of a statistical result may be quite elusive, a careful assessment of underlying assumptions is central in medicine as well as in other fields where a statistical method is applied. Unfortunately, a careful assessment of underlying assumptions is missing in many papers, including those published in top class journals. In this paper, it is shown that nonparametric methods are good alternatives to parametric methods when the assumptions for the latter ones are not satisfied. A key point to solve the problem of the misuse of statistics in the medical literature is that all journals have their own statisticians to review the statistical method/analysis section in each submitted paper.