元分析和偏相关系数:权重问题

IF 5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Research Synthesis Methods Pub Date : 2023-12-29 DOI:10.1002/jrsm.1697
Sanghyun Hong, W. Robert Reed
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引用次数: 0

摘要

本研究以 Stanley 和 Doucouliagos 最近发表的论文(Research Synthesis Methods 2023;14;515-519)的模拟框架为基础。S&D利用模拟提出了一个论点:使用偏相关系数(PCC)进行荟萃分析时,在构建固定效应和随机效应估计的权重时,应采用偏相关系数标准误差的 "次优 "估计器。我们担心他们的模拟和随后的建议可能会给元分析者造成误导。虽然他们所推荐的估计器在蒙特卡罗框架中占据了 "正确 "公式的优势,但还有其他估计器表现得更好。我们的结论是,在为使用 PCC 的元分析提出最佳实践建议之前,还需要进行更多的研究。
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Meta-analysis and partial correlation coefficients: A matter of weights

This study builds on the simulation framework of a recent paper by Stanley and Doucouliagos (Research Synthesis Methods 2023;14;515–519). S&D use simulations to make the argument that meta-analyses using partial correlation coefficients (PCCs) should employ a “suboptimal” estimator of the PCC standard error when constructing weights for fixed effect and random effects estimation. We address concerns that their simulations and subsequent recommendation may give meta-analysts a misleading impression. While the estimator they promote dominates the “correct” formula in their Monte Carlo framework, there are other estimators that perform even better. We conclude that more research is needed before best practice recommendations can be made for meta-analyses with PCCs.

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来源期刊
Research Synthesis Methods
Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES
CiteScore
16.90
自引率
3.10%
发文量
75
期刊介绍: Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.
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