The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study
Joint Authors
Zare, Najaf
Ayatollahi, Seyyed Mohammad Taghi
Dehesh, Tania
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-01
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Background.
Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular.
Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency.
Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach.
Methods.
We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study.
Result.
Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures.
The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC.
Conclusion.
This study highlights advantages of MGLS meta-analysis on UM approach.
The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
American Psychological Association (APA)
Dehesh, Tania& Zare, Najaf& Ayatollahi, Seyyed Mohammad Taghi. 2015. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1058000
Modern Language Association (MLA)
Dehesh, Tania…[et al.]. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1058000
American Medical Association (AMA)
Dehesh, Tania& Zare, Najaf& Ayatollahi, Seyyed Mohammad Taghi. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1058000
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1058000