Ontology highlight
ABSTRACT:
SUBMITTER: Pan L
PROVIDER: S-EPMC7021245 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Pan Lanfeng L Li Yehua Y He Kevin K Li Yanming Y Li Yi Y
Journal of multivariate analysis 20191015
We propose a new class of generalized linear mixed models with Gaussian mixture random effects for clustered data. To overcome the weak identifiability issues, we fit the model using a penalized Expectation Maximization (EM) algorithm, and develop sequential locally restricted likelihood ratio tests to determine the number of components in the Gaussian mixture. Our work is motivated by an application to nationwide kidney transplant center evaluation in the United States, where the patient-level ...[more]