Evidence map›Paper›PMID 26573817›Full record

ArticleBMC medical research methodology2015

Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies.

Christian Röver, Guido Knapp, Tim Friede

Abstract read
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In one paragraph

Article in BMC medical research methodology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 254 papers, 116 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
254citing papers in PubMed, 116 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

254 citing papers in PubMed, 116 syntheses or guidelines pooled it.

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  4. Retinal and choroidal optical coherence tomography findings in gestational diabetes mellitus: a systematic review and meta-analysis.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
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  7. Oral appliances for obstructive sleep apnoea in adults.The Cochrane database of systematic reviews · 2026
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  17. Do thyroid nodules in the isthmus carry a higher risk of malignancy? A systematic review and meta-analysis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
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194 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.

Christian RöverDepartment of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Göttingen, 37073, Germany. christian.roever@med.uni-goettingen.de.
Guido KnappDepartment of Statistics, TU Dortmund University, Dortmund, 44221, Germany. guido.knapp@tu-dortmund.de.
Tim FriedeDepartment of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Göttingen, 37073, Germany. tim.friede@med.uni-goettingen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRandom-effects meta-analysis is commonly performed by first deriving an estimate of the between-study variation, the heterogeneity, and subsequently using this as the basis for combining results, i.e., for estimating the effect, the figure of primary interest. The heterogeneity variance estimate however is commonly associated with substantial uncertainty, especially in contexts where there are only few studies available, such as in small populations and rare diseases.

methodsConfidence intervals and tests for the effect may be constructed via a simple normal approximation, or via a Student-t distribution, using the Hartung-Knapp-Sidik-Jonkman (HKSJ) approach, which additionally uses a refined estimator of variance of the effect estimator. The modified Knapp-Hartung method (mKH) applies an ad hoc correction and has been proposed to prevent counterintuitive effects and to yield more conservative inference. We performed a simulation study to investigate the behaviour of the standard HKSJ and modified mKH procedures in a range of circumstances, with a focus on the common case of meta-analysis based on only a few studies.

resultsThe standard HKSJ procedure works well when the treatment effect estimates to be combined are of comparable precision, but nominal error levels are exceeded when standard errors vary considerably between studies (e.g. due to variations in study size). Application of the modification on the other hand yields more conservative results with error rates closer to the nominal level. Differences are most pronounced in the common case of few studies of varying size or precision.

conclusionsUse of the modified mKH procedure is recommended, especially when only a few studies contribute to the meta-analysis and the involved studies' precisions (standard errors) vary.

Indexed as

Meta-Analysis as TopicModels, StatisticalAlgorithmsComputer SimulationConfidence IntervalsHumansSample SizeUncertainty

Identifiers

PMID26573817
PMCPMC4647507

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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.