Evidence map›Paper›PMID 32728636›Full record

ArticleHealth science reports2020

Arcsine-based transformations for meta-analysis of proportions: Pros, cons, and alternatives.

Lifeng Lin, Chang Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Health science reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers, 88 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
162citing papers in PubMed, 88 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

162 citing papers in PubMed, 88 syntheses or guidelines pooled it.

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102 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

2 authors.

Lifeng LinDepartment of Statistics Florida State University Tallahassee Florida.ORCID https://orcid.org/0000-0002-3562-9816
Chang XuDepartment of Population Medicine College of Medicine, Qatar University Doha Qatar.

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
Statistical Methods and Software for Multivariate Meta-analysisR01LM012982 · NLM · UNIVERSITY OF MINNESOTA · PI LIN, LIFENG, SIEGEL, LIANNE · 2019 to 2022
$1.3M
NCATS NIH HHS UL1 TR001427NLM NIH HHS R01 LM012982
6 · The paper itself

Abstract

Meta-analyses have been increasingly used to synthesize proportions (eg, disease prevalence) from multiple studies in recent years. Arcsine-based transformations, especially the Freeman-Tukey double-arcsine transformation, are popular tools for stabilizing the variance of each study's proportion in two-step meta-analysis methods. Although they offer some benefits over the conventional logit transformation, they also suffer from several important limitations (eg, lack of interpretability) and may lead to misleading conclusions. Generalized linear mixed models and Bayesian models are intuitive one-step alternative approaches, and can be readily implemented via many software programs. This article explains various pros and cons of the arcsine-based transformations, and discusses the alternatives that may be generally superior to the currently popular practice.

Indexed as

arcsine‐based transformationBayesian modelgeneralized linear mixed modelmeta‐analysisproportion

Identifiers

PMID32728636
PMCPMC7384291

What OpenQuestion holds

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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.