Evidence map›Paper›PMID 19547734›Full record

ArticleDeutsches Arzteblatt international2009

Confidence interval or p-value?: part 4 of a series on evaluation of scientific publications.

Jean-Baptist du Prel, Gerhard Hommel, Bernd Röhrig, Maria Blettner

Abstract readComparative StudyEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Deutsches Arzteblatt international, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
174citing papers in PubMed, 14 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

174 citing papers in PubMed, 14 syntheses or guidelines pooled it.

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114 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

4 authors.

Jean-Baptist du PrelJohannes Gutenberg-Universität Mainz, Mainz, Germany. duprel@zpp.klinik.uni-mainz.de
Gerhard Hommel
Bernd Röhrig
Maria Blettner

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn understanding of p-values and confidence intervals is necessary for the evaluation of scientific articles. This article will inform the reader of the meaning and interpretation of these two statistical concepts.

methodsThe uses of these two statistical concepts and the differences between them are discussed on the basis of a selective literature search concerning the methods employed in scientific articles. RESULTS/

conclusionsP-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide information about a range in which the true value lies with a certain degree of probability, as well as about the direction and strength of the demonstrated effect. This enables conclusions to be drawn about the statistical plausibility and clinical relevance of the study findings. It is often useful for both statistical measures to be reported in scientific articles, because they provide complementary types of information.

Indexed as

AlgorithmsConfidence IntervalsData Interpretation, StatisticalPeriodicals as TopicScienceReproducibility of ResultsSensitivity and Specificityclinical researchconfidence intervalpublicationsp-valuestatistics

Identifiers

PMID19547734
PMCPMC2689604

What OpenQuestion holds

Textmetadata
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.