Joint regression analysis of mixed-type outcome data via efficient scores

DOI10.1016/J.CSDA.2018.02.008zbMath1469.62119OpenAlexW2803023053WikidataQ129929232 ScholiaQ129929232MaRDI QIDQ1662937

Scott Marchese, Guoqing Diao

Publication date: 20 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.02.008

zbMATH Keywords

generalized estimating equationsefficient scoreBonferroni correctionmixed-type datamultiplier bootstrap

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Uses Software

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• geepack
• Rcpp
• RcppEigen

Cites Work

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• Longitudinal data analysis using generalized linear models
• Nonlinear shrinkage estimation of large-dimensional covariance matrices
• Density ratio model for multivariate outcomes
• Weak convergence and empirical processes. With applications to statistics
• Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
• Asymptotic inference for high-dimensional data
• Correlated data analysis: modeling, analytics, and applications
• On generalised estimating equations for vector regression
• Joint Estimation of the Mean and Error Distribution in Generalized Linear Models
• A Primer on Copulas for Count Data
• Multivariate Statistics

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