5 papers · 1 filter
Random Effects Misspecification and its Consequences for Prediction in Generalized Linear Mixed Models
Quan Vu, Francis K. C. Hui, Samuel Muller +1
When fitting generalized linear mixed models (GLMMs), one important decision to make relates to the choice of the random effects distribution. As the random effects are unobserved,…
Joint Mean and Correlation Regression Models for Multivariate Data
Zhi Yang Tho, Francis K. C. Hui, Tao Zou
We propose a joint mean and correlation regression model for multivariate discrete and (semi-)continuous response data, that simultaneously regresses the mean of each response agai…
An Ising Similarity Regression Model for Modeling Multivariate Binary Data
Zhi Yang Tho, Francis K. C. Hui, Tao Zou
Understanding the dependence structure between response variables is an important component in the analysis of correlated multivariate data. This article focuses on modeling depend…
Likelihood-based surrogate dimension reduction
Linh H. Nghiem, Francis K. C. Hui, Samuel Mueller +1
We consider the problem of surrogate sufficient dimension reduction, that is, estimating the central subspace of a regression model, when the covariates are contaminated by measure…
Cokrig-and-Regress for Spatially Misaligned Environmental Data
Z. Y. Tho, F. K. C. Hui, A. H. Welsh +1
Spatially misaligned data, where the response and covariates are observed at different spatial locations, commonly arise in many environmental studies. Much of the statistical lite…