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元回归模型中的影响诊断。

Influence diagnostics in meta-regression model.

机构信息

School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, 650221, China.

Department of Biostatistics, The University of Washington, Seattle, WA, 98195, USA.

出版信息

Res Synth Methods. 2017 Sep;8(3):343-354. doi: 10.1002/jrsm.1247. Epub 2017 Jul 18.

Abstract

This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology.

摘要

本文研究了元回归模型中的影响诊断,包括病例删除诊断和局部影响分析。我们推导出了用于估计回归系数和异质性方差的子集删除公式,并得到了相应的影响度量。分别考虑了元回归中的德西蒙和莱尔德估计和最大似然估计方法,以得出结果。定义了内部和外部残差和杠杆度量。探索了基于病例权重摄动方案、响应摄动方案、协变量摄动方案和方差内摄动方案的局部影响分析。我们引入了一种通过同时摄动响应、协变量和方差内来获得局部影响度量的方法,该方法具有能够比较来自不同摄动的有影响研究的影响大小的优点。通过一个例子来说明所提出的方法。

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