論文

査読有り 国際誌
2017年6月

Synthesis of linear regression coefficients by recovering the within-study covariance matrix from summary statistics

Research Synthesis Methods
  • Daisuke Yoneoka
  • ,
  • Masayuki Henmi

8
2
開始ページ
212
終了ページ
219
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1002/jrsm.1228
出版者・発行元
WILEY

Copyright © 2016 John Wiley & Sons, Ltd. Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd.

Web of Science ® 被引用回数 : 3

リンク情報
DOI
https://doi.org/10.1002/jrsm.1228
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/27987264
Scopus
https://www.scopus.com/record/display.uri?eid=2-s2.0-85020640858&origin=inward
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000403317900007&DestApp=WOS_CPL
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85020640858&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85020640858&origin=inward

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