Evidence map›Paper›PMID 35841123›Full record

ArticleResearch synthesis methods2022

MA-cont:pre/post effect size: An interactive tool for the meta-analysis of continuous outcomes using R Shiny.

Katerina Papadimitropoulou, Richard D Riley, Olaf M Dekkers, Theo Stijnen, Saskia le Cessie

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In one paragraph

Article in Research synthesis methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 5 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, 5 syntheses or guidelines pooled it.

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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

5 authors.

Katerina PapadimitropoulouClinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-5732-4044
Richard D RileyCentre for Prognosis Research, Research Institute for Primary Care & Health Sciences, Keele University, Keele, UK.
Olaf M DekkersClinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Theo StijnenBiomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Saskia le CessieClinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meta-analysis is a widely used methodology to combine evidence from different sources examining a common research phenomenon, to obtain a quantitative summary of the studied phenomenon. In the medical field, multiple studies investigate the effectiveness of new treatments and meta-analysis is largely performed to generate the summary (average) treatment effect. In the meta-analysis of aggregate continuous outcomes measured in a pretest-posttest design using differences in means as the effect measure, a plethora of methods exist: analysis of final (follow-up) scores, analysis of change scores and analysis of covariance. Specialised and general-purpose statistical software is used to apply the various methods, yet, often the choice among them depends on data availability and statistical affinity. We present a new web-based tool, MA-cont:pre/post effect size, to conduct meta-analysis of continuous data assessed pre- and post-treatment using the aforementioned approaches on aggregate data and a more flexible approach of generating and analysing pseudo individual participant data. The interactive web environment, available by R Shiny, is used to create this free-to-use statistical tool, requiring no programming skills by the users. A basic statistical understanding of the methods running in the background is a prerequisite and we encourage the users to seek advice from technical experts when necessary.

Indexed as

Meta-Analysis as TopicSoftwareHumansANCOVAbaseline imbalancepseudo individual participant datashiny

Identifiers

PMID35841123
PMCPMC9546083

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.