The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Arcsine‐based transformations for meta‐analysis of proportions: Pros, cons, and alternatives
Open accessAbstract
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.
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Cites
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“For example, metaanalysts frequently use the forest plot to visualize the distributions of study-specific estimates,(56) and the funnel plot to assess potential publication bias or small-study effects.(57,58) Both plots depend on each”
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“Besides the arcsine-based transformations, the log and logit transformations are also frequently used for proportions.(10,20,21) Their formulas are more straightforward: the log transformation is yi = g (pi) = logpi, with variance vi = 1/ei − 1/ni, and the logit transformation is yi = g(pi) = log[pi/(1 − pi)], with va…”
Method
Research works printed but not linked: 3
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Cited by
Teo, R. H., Cheng, W. H., Cheng, L. J., Lau, Y., & Lau, S. T. (2023) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2022.104904 · Cited by 160
Qiu, X., Nergiz, A. I., Maraolo, A. E., Bogoch, I. I., Low, N., & Cevik, M. (2021) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.01.011 · Cited by 135
Ribeiro, F., Teixeira-Santos, A. C., Caramelli, P., & Leist, A. K. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2022.101703 · Cited by 114
“Accordingly, the random effects method was used to estimate the pooled prevalence using the Freeman-Tukey double arcsine transformation that stabilizes the variance of each study’s proportion (Lin and Xu, 2020).”
MethodHuang, G., Chu, H., Chen, R., Liu, D., Banda, K. J., O’Brien, A. P., Jen, H.-J., Chiang, K.-J., Chiou, J.-F., & Chou, K.-R. (2022) · Journal of Global Health · doi:10.7189/jogh.12.05028 · Cited by 64
Stegen, H., Duppen, D., Savieri, P., Stas, L., Pan, H., Aartsen, M., Callewaert, H., Dierckx, E., & De Donder, L. (2024) · International Psychogeriatrics · doi:10.1017/s1041610224000425 · Cited by 42
Metadata
- Authors
- Lin, L., & Xu, C.
- Venue
- Health Science Reports
- Publisher
- Wiley
- Published
- 2020-07-27
- Volume
- 3
- Issue
- 3
- Pages
- e178-e178
- ISSN
- 2398-8835 (ISSN-L)
- OpenAlex
- W3044366033
- Cited by
- 339
- References
- 59
- FWCI
- 24.30
- Type
- journal article
- Language
- en
- Open access
- gold
- Funders
- National Center for Advancing Translational Sciences (UL1 TR001427)
- U.S. National Library of Medicine (R01 LM012982)
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