Cited by 140Statistical Methods in Clinical TrialsStatistical Methods in EpidemiologyStatistical Methods and Bayesian Inference

Multiplicity Considerations in Clinical Trials

Dmitrienko, Alex, D’Agostino, Ralph B.·2018·New England Journal of Medicine

Abstract

Making multiple comparisons increases the likelihood that a chance association could be interpreted as causal. A number of statistical approaches can facilitate the precise interpretation of clinical trial results.

Integrity signals

Registry

Crossref · 10.1056/nejmra1709701

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Dmitrienko, A., & D’Agostino, R. B.
Affiliations
Boston University (US)
Venue
New England Journal of Medicine
Published
2018-05-31
Volume
378
Issue
22
Pages
2115-2122
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W2806596191
Cited by
140
References
30
Citations by year
2026: 14 · 2025: 18 · 2024: 16 · 2023: 6 · 2022: 22 · 2021: 22 · 2020: 19 · 2019: 16 · 2018: 7
FWCI
2.19
Type
journal article
Language
en
Open access
closed
Locations
  • New England Journal of Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords
multiplicity, multiple comparisons, clinical trials, statistical significance, false positives, causal inference
MeSH terms
Data Interpretation, Statistical, Humans, Research Design, Statistics as Topic, Causality, Clinical Trials, Phase III as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review