Likelihood-Based Inference on Genetic Variance Component with a Hierarchical Poisson Generalized Linear Mixed Model

Permutation-based variance component test in generalized linear mixed model with application to multilocus genetic association study

BACKGROUND In many medical studies the likelihood ratio test (LRT) has been widely applied to examine whether the random effects variance component is zero within the mixed effects models framework; whereas little work about likelihood-ratio based variance component test has been done in the generalized linear mixed models (GLMM), where the response is discrete and the log-likelihood cannot be ...

Likelihood inference in generalized linear mixed measurement error models

The generalized linear mixed models (GLMMs) for clustered data are studied when covariates aremeasured with error. Themost conventional measurement error models are based on either linear mixed models (LMMs) or GLMMs. Even without the measurement error, the frequentist analysis of LMM, and particularly of GLMM, is computationally difficult. On the other hand, Bayesian analysis of LMM and GLMM i...

Restricted likelihood inference for generalized linear mixed models

Conditional Likelihood Inference in Generalized Linear Mixed Models

Consider a generalized linear model with a canonical link function, containing both fixed and random effects. In this paper, we consider inference about the fixed effects based on a conditional likelihood function. It is shown that this conditional likelihood function is valid for any distribution of the random effects and, hence, the resulting inferences about the fixed effects are insensitive...

Variance Component Testing in Generalized Linear Mixed Models

Generalized linear mixed models (GLMM) are used in situations where a number of characteristics (covariates) affect a nonnormal response variable and the responses are correlated. For example, in a number of biological applications, the responses are correlated due to common genetic or environmental factors. In many applications, the magnitude of the variance components corresponding to one or ...