Who is afraid of non-normal data? Choosing between parametric and non-parametric tests
Who is afraid of non-normal data? Choosing between parametric and non-parametric tests
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DOI：
10.1530/eje-19-0922
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发表时间：
2020-02-01
影响因子：
5.8
通讯作者：
Dekkers, Olaf M.
中科院分区：
文献类型：
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作者：
le Cessie, Saskia;Goeman, Jelle J.;Dekkers, Olaf M.
在统计比较两组之间的结果时，研究人员必须决定是使用参数方法，如t检验，还是使用非参数方法，如Mann-Whitney检验。例如，在内分泌学中，许多研究比较各组之间或不同时间点的激素水平。许多论文应用非参数检验来比较组。我们将解释非参数测试在医学研究中有明显的缺点，这是好消息，它们通常是不必要的。
When statistically comparing outcomes between two groups, researchers have to decide whether to use parametric methods, such as the t-test, or non-parametric methods, like the Mann-Whitney test. In endocrinology, for example, many studies compare hormone levels between groups, or at different points in time. Many papers apply nonparametric tests to compare groups. We will explain that non-parametric tests have clear drawbacks in medical research, and, that's the good news, they are often not necessary.