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Copula-Based Estimation Methods for a Common Mean Vector for Bivariate Meta-Analyses. Symmetry (Basel) 2022. [DOI: 10.3390/sym14020186] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Traditional bivariate meta-analyses adopt the bivariate normal model. As the bivariate normal distribution produces symmetric dependence, it is not flexible enough to describe the true dependence structure of real meta-analyses. As an alternative to the bivariate normal model, recent papers have adopted “copula” models for bivariate meta-analyses. Copulas consist of both symmetric copulas (e.g., the normal copula) and asymmetric copulas (e.g., the Clayton copula). While copula models are promising, there are only a few studies on copula-based bivariate meta-analysis. Therefore, the goal of this article is to fully develop the methodologies and theories of the copula-based bivariate meta-analysis, specifically for estimating the common mean vector. This work is regarded as a generalization of our previous methodological/theoretical studies under the FGM copula to a broad class of copulas. In addition, we develop a new R package, “CommonMean.Copula”, to implement the proposed methods. Simulations are performed to check the proposed methods. Two real dataset are analyzed for illustration, demonstrating the insufficiency of the bivariate normal model.
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Sharifonnasabi Z, Alamatsaz MH, Kazemi I. A large class of new bivariate copulas and their properties. BRAZ J PROBAB STAT 2018. [DOI: 10.1214/17-bjps351] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Shih JH, Emura T. Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula. Comput Stat 2018. [DOI: 10.1007/s00180-018-0804-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Shih JH, Emura T. Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula. Stat Pap (Berl) 2016. [DOI: 10.1007/s00362-016-0865-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Zargar M, Jabbari Nooghabi H, Amini M. Test of Independence for Baker’s Bivariate Distributions. COMMUN STAT-SIMUL C 2016. [DOI: 10.1080/03610918.2014.917676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- M. Zargar
- Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran
| | - H. Jabbari Nooghabi
- Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran
| | - M. Amini
- Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran
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Zargar M, Jabbari H, Amini M. Comparing the empirical powers of several independence tests in generalized FGM family. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2016. [DOI: 10.5351/csam.2016.23.3.215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- M. Zargar
- Department of Statistics, Ferdowsi University of Mashhad, Iran
| | - H. Jabbari
- Department of Statistics, Ferdowsi University of Mashhad, Iran
| | - M. Amini
- Department of Statistics, Ferdowsi University of Mashhad, Iran
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Pathak AK, Vellaisamy P. Various measures of dependence of a new asymmetric generalized Farlie–Gumbel–Morgenstern copulas. COMMUN STAT-THEOR M 2015. [DOI: 10.1080/03610926.2014.942428] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Domma F, Giordano S. A copula-based approach to account for dependence in stress-strength models. Stat Pap (Berl) 2012. [DOI: 10.1007/s00362-012-0463-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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