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Robust confidence intervals for trend estimation in meta-analysis with publication bias

Lookup NU author(s): Hong Lu, Peng Yin, Dr Jian Shi

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Abstract

Confidence interval (CI) is very useful for trend estimation in meta-analysis. It provides a type of interval estimate of the regression slope as well as an indicator of the reliability of the estimate. Thus a precise calculation of confidence interval at an expected level is important. It is always difficult to explicitly quantify the CIs when there is publication bias in meta-analysis. Various CIs have been proposed, including the most widely used DerSimonian-Laird CI and the recently proposed Henmi-Copas CI. The latter provides a robust solution when there are non-ignorable missing data due to publication bias. In this paper we extended the idea into meta-analysis for trend estimation. We applied the method in different scenarios and showed that this type of CI is more robust than the others.


Publication metadata

Author(s): Lu H, Yin P, Yue RX, Shi JQ

Publication type: Article

Publication status: Published

Journal: Journal of Applied Statistics

Year: 2015

Volume: 42

Issue: 12

Pages: 2715-2733

Print publication date: 01/12/2015

Online publication date: 05/08/2015

Acceptance date: 04/05/2015

ISSN (print): 0266-4763

ISSN (electronic): 1360-0532

Publisher: Taylor & Francis

URL: http://dx.doi.org/10.1080/02664763.2015.1048672

DOI: 10.1080/02664763.2015.1048672


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