| CommonMean.Copula-package {CommonMean.Copula} | R Documentation |
Common Mean Vector under Copula Models
Description
Estimate bivariate common mean vector under copula models with known correlation. A maximum likelihood estimation procedure is employed. In the current version, available copulas are the Clayton, Gumbel, Frank, Farlie-Gumbel-Morgenstern (FGM), and normal copulas. See Shih et al. (2019) and Shih et al. (2021) for details under the FGM and general copulas, respectively.
Details
The method implemented in this package can be used for bivariate meta-analyses. See Shih et al. (2019) and Shih et al. (2021) for the example of bivariate entrance exam data analysis.
Author(s)
Jia-Han Shih
Maintainer: Jia-Han Shih <tommy355097@gmail.com>
References
Shih J-H, Konno Y, Chang Y-T, Emura T (2019) Estimation of a common mean vector in bivariate meta-analysis under the FGM copula, Statistics 53(3): 673-95.
Shih J-H, Konno Y, Emura T (2021-) Copula-based estimation methods for a common mean vector for bivariate meta-analyses, under review.