Evidence map›Paper›PMID 18005435›Full record

ArticleBMC medical research methodology2007

Reliability of journal impact factor rankings.

Darren C Greenwood

Abstract read
In one paragraph

Article in BMC medical research methodology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Bibliometric Analysis of Granger Causality Studies.Entropy (Basel, Switzerland) · 2023
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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

1 author.

Darren C GreenwoodBiostatistics Unit, Centre for Epidemiology & Biostatistics, University of Leeds, Leeds, UK. d.c.greenwood@leeds.ac.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundJournal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises.

methodsBased on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators.

resultsIntervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals.

conclusionDecisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate.

Indexed as

BibliometricsBiomedical ResearchHumansPeriodicals as TopicProbabilityReproducibility of Results

Identifiers

PMID18005435
PMCPMC2206035

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.