Metaprop: a Stata command to perform meta-analysis of binomial data
By V. Nyaga, M. Arbyn, Marc Aerts. Archives of Public Health, 2014
1,959 citations recorded by the source corpus.
BackgroundMeta-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.MethodsMetaprop 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.ResultsThe 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%).ConclusionBy 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.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/9b6c04ec1666a06b932621976f60e05e92457374
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In Artificial Intelligence
In Statistics and Probability
- Luke A. McGuinness
- J. Dickson
- K. Jomar
- P. Taylor
- Rebecca L. Forrester
- Ujala Shahmalak
- K. Dhingra
- M. Arbyn
Citations in the corpus
- A meta-analysis of the prevalence of different functions of non-suicidal self-injury. (2018, methodology): “Meta-analyses of prevalence were performed using STATA version 14 (StataCorp, 2015) via the Metaprop command (Nyaga et al., 2014).”
- Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta‐analysis (2021, methodology): “The metaprop command in Stata was used to calculate the overall pooled estimates with inverse-variance weights obtained from random-effect meta-analysis models.(23) For subgroup analyses, heterogeneity was assessed using the I(2)”
- The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries (2020, methodology): “Analysis The pooled prevalence of symptoms were estimated using the metaprop package [27] in Stata/ MP v15.”