Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

BACKGROUND: Despite regular criticisms of null hypothesis significance testing (NHST), a focus on testing persists, sometimes in the belief to get published and sometimes encouraged by journal reviewers. This paper aims to demonstrate known key limitations of NHST using simple nontechnical illustrations. DESIGN: The first illustration is based on simulated data of 20 000 studies that compare two groups for an outcome event. The true effect size (difference in event rates) and sample size (20-100 per group) were varied. The second illustration used real data from a meta-analysis on alpha-blockers for the treatment of ureteric stones. RESULTS: The simulations demonstrated the large between-study variability in P-values (range between

Original publication

DOI

10.1111/eci.12912

Type

Journal article

Journal

Eur j clin invest

Publication Date

05/2018

Volume

48

Keywords

confidence intervals, effect size, null hypothesis significance testing, reporting, statistical significance, study design, Biomedical Research, Data Interpretation, Statistical, Models, Statistical, Probability, Sample Size, Uncertainty