J
John P. A. Ioannidis
Researcher at Stanford University
Publications - 1409
Citations - 231769
John P. A. Ioannidis is an academic researcher from Stanford University. The author has contributed to research in topics: Randomized controlled trial & Population. The author has an hindex of 185, co-authored 1311 publications receiving 193612 citations. Previous affiliations of John P. A. Ioannidis include National Institutes of Health & Boston University.
Papers
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The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +10 more
TL;DR: An Explanation and Elaboration of the PRISMA Statement is presented and updated guidelines for the reporting of systematic reviews and meta-analyses are presented.
Journal ArticleDOI
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration
Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +9 more
TL;DR: The meaning and rationale for each checklist item is explained, and an example of good reporting is included and, where possible, references to relevant empirical studies and methodological literature are included.
Journal ArticleDOI
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration
Alessandro Liberati,Douglas G. Altman,Jennifer Tetzlaff,Cynthia D. Mulrow,Peter C Gøtzsche,John P. A. Ioannidis,Mike Clarke,Mike Clarke,Philip J. Devereaux,Jos Kleijnen,David Moher +10 more
TL;DR: This Explanation and Elaboration document explains the meaning and rationale for each checklist item and includes an example of good reporting and, where possible, references to relevant empirical studies and methodological literature.
Journal ArticleDOI
Power failure: why small sample size undermines the reliability of neuroscience
Katherine S. Button,John P. A. Ioannidis,Claire Mokrysz,Brian A. Nosek,Jonathan Flint,Emma S J Robinson,Marcus R. Munafò +6 more
TL;DR: It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
Why Most Published Research Findings Are False
TL;DR: In this paper, the authors discuss the implications of these problems for the conduct and interpretation of research and suggest that claimed research findings may often be simply accurate measures of the prevailing bias.