Bivariate beta-binomial model using Gaussian copula for bivariate meta-analysis of two binary outcomes with low incidence
DOI10.1007/S42081-019-00037-ZzbMath1436.62190OpenAlexW2921311622WikidataQ128264391 ScholiaQ128264391MaRDI QIDQ2303486
Kazushi Maruo, Yusuke Yamaguchi
Publication date: 4 March 2020
Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s42081-019-00037-z
Applications of statistics to biology and medical sciences; meta analysis (62P10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Generalized linear models (logistic models) (62J12)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An introduction to copulas.
- On the simultaneous associativity of F(x,y) and x+y-F(x,y)
- Dependence Modeling with Copulas
- Bivariate Exponential Distributions
- Exact and efficient inference procedure for meta-analysis and its application to the analysis of independent 2 x 2 tables with all available data but without artificial continuity correction
- Meta‐analysis of clinical trials with rare events
- Joint Regression Analysis of Correlated Data Using Gaussian Copulas
- An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown
- Some bivariate uniform distributions
- A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
- Multivariate Dispersion Models Generated From Gaussian Copula
This page was built for publication: Bivariate beta-binomial model using Gaussian copula for bivariate meta-analysis of two binary outcomes with low incidence
