Evidence map›Paper›PMID 32441650›Full record

ArticleeLife2020

Addressing selective reporting of experiments through predefined exclusion criteria.

Kleber Neves, Olavo B Amaral

Abstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
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

2 authors.

Kleber NevesInstitute of Medical Biochemistry Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.ORCID 0000-0001-9519-4909
Olavo B AmaralInstitute of Medical Biochemistry Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.ORCID 0000-0002-4299-8978

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pressure for every research article to tell a clear story often leads researchers in the life sciences to exclude experiments that 'did not work' when they write up their results. However, this practice can lead to reporting bias if the decisions about which experiments to exclude are taken after data have been collected and analyzed. Here we discuss how to balance clarity and thoroughness when reporting the results of research, and suggest that predefining the criteria for excluding experiments might help researchers to achieve this balance.

Indexed as

BiasHumansPublicationsResearchSciencebiasbiochemistrychemical biologyneurosciencenonepreregistrationreplicationreproducibilityscience forumvalidation

Identifiers

PMID32441650
PMCPMC7244322

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.