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

Saskia le Cessie, Jelle J. Goeman, Olaf M Dekkers

2020European Journal of Endocrinology114 citationsDOIOpen Access PDF

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.

Topics & Concepts

Parametric statisticsMann–Whitney U testNonparametric statisticsTest (biology)MedicineParametric modelInternal medicineStatisticsEconometricsComputer scienceMathematicsBiologyPaleontologyStatistical Methods in Clinical Trials
Who is afraid of non-normal data? Choosing between parametric and non-parametric tests | Litcius