Meta-analysis and partial correlation coefficients: A matter of weights

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
{"title":"Meta-analysis and partial correlation coefficients: A matter of weights","authors":"Sanghyun Hong,&nbsp;W. Robert Reed","doi":"10.1002/jrsm.1697","DOIUrl":null,"url":null,"abstract":"<p>This study builds on the simulation framework of a recent paper by Stanley and Doucouliagos (<i>Research Synthesis Methods</i> 2023;14;515–519). S&amp;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.</p>","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jrsm.1697","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research Synthesis Methods","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jrsm.1697","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
元分析和偏相关系数:权重问题
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Automation tools to support undertaking scoping reviews. Reduce, reuse, recycle: Introducing MetaPipeX, a framework for analyses of multi-lab data. A comparison of two models for detecting inconsistency in network meta-analysis. Calculating the power of a planned individual participant data meta-analysis to examine prognostic factor effects for a binary outcome. Considerations for conducting systematic reviews: A follow-up study to evaluate the performance of various automated methods for reference de-duplication.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1