Robust transformation mixed‐effects models for longitudinal continuous proportional data

DOI10.1002/cjs.10015zbMath1176.62018OpenAlexW2028492170MaRDI QIDQ5192951

Zhenguo Qiu, Peng Zhang, Peter X.-K. Song, Yuejiao Fu

Publication date: 10 August 2009

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2027.42/63085

zbMATH Keywords

outliersrobustnesslogit-\(t\) distributionlogit-normal distribution

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (6)

On a multivariate regression model for rates and proportions ⋮ Generalized bounds for active subspaces ⋮ On a heavy-tailed parametric quantile regression model for limited range response variables ⋮ Analysis of incomplete longitudinal data with informative drop‐out and outliers ⋮ A spatial augmented beta regression model for periodontal proportion data ⋮ A new approach for joint modelling of longitudinal measurements and survival times with a cure fraction

Cites Work

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• Correlated data analysis: modeling, analytics, and applications
• Simplex Mixed‐Effects Models for Longitudinal Proportional Data
• Maximum Likelihood Algorithms for Generalized Linear Mixed Models
• Marginal Models for Longitudinal Continuous Proportional Data
• Multivariate T-Distributions and Their Applications

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