Evidence map›Paper›PMID 31111673›Full record

ArticleResearch synthesis methods2019

A new justification of the Hartung-Knapp method for random-effects meta-analysis based on weighted least squares regression.

Robbie C M van Aert, Dan Jackson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Research synthesis methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 25 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 25 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

48 citing papers in PubMed, 25 syntheses or guidelines pooled it.

  1. Ceftriaxone for methicillin-susceptibleAnnals of medicine · 2026
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  7. Cost-efficiency of digital versus conventional workflow for removable complete dentures: A systematic review and meta-analysis.Journal of prosthodontics : official journal of the American College of Prosthodontists · 2026
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  16. Exercise-based interventions targeting balance and falls in people with COPD: a systematic review and meta-analysis.European respiratory review : an official journal of the European Respiratory Society · 2024
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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

2 authors.

Robbie C M van AertMethodology and Statistics, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0001-6187-0665
Dan JacksonStatistical Innovation Group, Advanced Analytics Centre, AstraZeneca, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-4963-8123

Funding

European Research Council 726361 (IMPROVE)Netherlands Organization for Scientific Research (NWO) 406-13-050
6 · The paper itself

Abstract

The Hartung-Knapp method for random-effects meta-analysis, that was also independently proposed by Sidik and Jonkman, is becoming advocated for general use. This method has previously been justified by taking all estimated variances as known and using a different pivotal quantity to the more conventional one when making inferences about the average effect. We provide a new conceptual framework for, and justification of, the Hartung-Knapp method. Specifically, we show that inferences from fitted random-effects models, using both the conventional and the Hartung-Knapp method, are equivalent to those from closely related intercept only weighted least squares regression models. This observation provides a new link between Hartung and Knapp's methodology for meta-analysis and standard linear models, where it can be seen that the Hartung-Knapp method can be justified by a linear model that makes a slightly weaker assumption than taking all variances as known. This provides intuition for why the Hartung-Knapp method has been found to perform better than the conventional one in simulation studies. Furthermore, our new findings give more credence to ad hoc adjustments of confidence intervals from the Hartung-Knapp method that ensure these are at least as wide as more conventional confidence intervals. The conceptual basis for the Hartung-Knapp method that we present here should replace the established one because it more clearly illustrates the potential benefit of using it.

Indexed as

Least-Squares AnalysisMeta-Analysis as TopicAlgorithmsComputer SimulationData Interpretation, StatisticalLinear ModelsResearch DesignSample SizeHartung-Knapp modificationmeta-analysismeta-regressionrandom-effects weighted least squares regression

Identifiers

PMID31111673
PMCPMC6973024

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.