Metaprop: a Stata command to perform meta-analysis of binomial data
Open accessAbstract
BACKGROUND: Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. METHODS: Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. RESULTS: The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). CONCLUSION: By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.
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The Freeman-Tukey arcsine methodology was applied to ensure proportionate weight distribution to studies presenting extreme prevalence.
“To ensure proportionate weight distribution to studies presenting extreme prevalence (near 0 or 1), the Freeman-Tukey arcsine methodology was applied (Nyaga et al., 2014).”
From Maternal colonization or infection with extended-spectrum beta-lactamase-producing Enterobacteriaceae in Africa: A systematic review and meta-analysis (2017) · cites this paper as Nyaga et al., 2014
The Results (Example two; page not provided) use the Freeman–Tukey transformation when some proportions are at or near 1, explaining that studies at 1 would otherwise be excluded and bias the pooled estimate. The Methods describe a weighted pooled estimate after transformation, but do not say the method ensures proportionate weight distribution to studies with extreme prevalence. (LLM, conf=0.84)
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- Authors
- Nyaga, V. N., Arbyn, M., & Aerts, M.
- Affiliations
- Institut Scientifique de Santé Publique (BE)
- Hasselt University (BE)
- Corresponding author
- Arbyn, Marc
- Venue
- Archives of Public Health
- Published
- 2014-11-10
- Volume
- 72
- Issue
- 1
- Pages
- 39-39
- ISSN
- 0778-7367 (ISSN-L)
- 2049-3258
- PMC
- PMC4373114
- OpenAlex
- W2133564174
- Cited by
- 2,139
- References
- 24
- Citations by year
- 2026: 88 · 2025: 157 · 2024: 249 · 2023: 272 · 2022: 286 · 2021: 321 · 2020: 296 · 2019: 166 · 2018: 133 · 2017: 91 · 2016: 61 · 2015: 16 · 2014: 1
- FWCI
- 15.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Archives of Public Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Document Server@UHasselt (UHasselt) (submittedVersion, cc-by)
- Funders
- European Commission (282562, 603019, FP7‐HEALTH‐2011)
- Vrije Universiteit Amsterdam
- FP7 Health (FP7-HEALTH-2011-282562, 603019)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- Stata command, binomial data, HPV prevalence, ASCUS, cold coagulation
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