Neurodegenerative diseases occur due to progressive and sometimes irreversible loss of
function and death of nerve cells. A great deal of effort is being made to understand the …

For multisource data, blocks of variable information from certain sources are likely missing.
Existing methods for handling missing data do not take structures of block-wise missing data …

Abstract Introduction Clinical Alzheimer's disease (AD) begins with mild cognitive
impairment (MCI) and progresses to mild, moderate, or severe dementia, constituting a …

Alzheimer's disease (AD) is an incurable and progressive disease that starts from mild
cognitive impairment and deteriorates over time. Examining the effects of patients' …

Abstract Hidden Markov models (HMMs) describe the relationship between two stochastic
processes: an observed process and an unobservable finite-state transition process. Owing …

Joint mixed membership modeling of multivariate longitudinal and survival data for learning
the individualized disease progressi Page 1 The Annals of Applied Statistics 2024, Vol. 18 …

This study considers a functional concurrent hidden Markov model. The proposed model
consists of two components. One is a transition model for elucidating how potential …

Abstract Hidden Markov models (HMMs) are widely used to analyze heterogeneous
longitudinal data owing to their capability to model dynamic heterogeneity. Early …

This paper presents a Bayesian adaptive group least absolute shrinkage and selection
operator method to conduct simultaneous model selection and estimation under …

Abstract Hidden Markov models (HMMs) describe the relationship between two stochastic
processes, namely, an observed outcome process and an unobservable finite-state …