Evidence map›Paper›PMID 27141478›Full record

ArticlePerspectives in clinical research

Common pitfalls in statistical analysis: The perils of multiple testing.

Priya Ranganathan, C S Pramesh, Marc Buyse

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Perspectives in clinical research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

88 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  4. Self-management interventions for cancer survivors: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2018
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28 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Priya RanganathanDepartment of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India.
C S PrameshDepartment of Surgical Oncology, Division of Thoracic Surgery, Tata Memorial Centre, Mumbai, Maharashtra, India.
Marc BuyseInternational Drug Development Institute, San Francisco, California, USA; Department of Biostatistics, Hasselt University, Hasselt, Belgium, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding. In this article, we look at the consequences of multiple testing and explore various methods to deal with this issue.

Indexed as

Biostatisticsdata interpretationmultiplicitystatistical significance

Identifiers

PMID27141478
PMCPMC4840791

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.