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المؤلفLin, Lifeng
المؤلفXu, Chang
تاريخ الإتاحة2021-02-07T10:13:55Z
تاريخ النشر2020-09-01
اسم المنشورHealth Science Reports
المعرّفhttp://dx.doi.org/10.1002/hsr2.178
الاقتباسLin, L, Xu, C. Arcsine‐based transformations for meta‐analysis of proportions: Pros, cons, and alternatives. Health Sci Rep. 2020; 9999:e178. https://doi.org/10.1002/hsr2.178
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091010819&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/17560
الملخص© 2020 The Authors. Health Science Reports published by Wiley Periodicals LLC. 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.
اللغةen
الناشرWiley Open Access
الموضوعarcsine-based transformation
Bayesian model
generalized linear mixed model
meta-analysis
proportion
العنوانArcsine-based transformations for meta-analysis of proportions: Pros, cons, and alternatives
النوعArticle
رقم العدد3
رقم المجلد3
ESSN2398-8835
dc.accessType Open Access


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