Who is afraid of non-normal data? Choosing between parametric and non-parametric tests

European Journal of Endocrinology, vol. 182, pp. E1–E3

Abstract

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 non-parametric 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.

Authors 3

1. Saskia le Cessie corresponding Aachen 1Departments of Clinical Epidemiology 2Departments of Biomedical Data Sciences

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   1Departments of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands

   2Departments of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands

2. Jelle J. Goeman Aachen 2Departments of Biomedical Data Sciences

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   2Departments of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands

3. Olaf M. Dekkers Aachen 1Departments of Clinical Epidemiology

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   1Departments of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands