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


Journal

European journal of endocrinology
ISSN: 1479-683X
Titre abrégé: Eur J Endocrinol
Pays: England
ID NLM: 9423848

Informations de publication

Date de publication:
Feb 2020
Historique:
received: 13 11 2019
accepted: 21 11 2019
entrez: 8 1 2020
pubmed: 8 1 2020
medline: 15 1 2020
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 31910149
doi: 10.1530/EJE-19-0922
pii: EJE-19-0922
doi:
pii:

Types de publication

Editorial

Langues

eng

Sous-ensembles de citation

IM

Pagination

E1-E3

Commentaires et corrections

Type : CommentIn

Auteurs

Saskia le Cessie (S)

Departments of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.
Departments of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.

Jelle J Goeman (JJ)

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

Olaf M Dekkers (OM)

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

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Classifications MeSH