Latent classification model for censored longitudinal binary outcome

DOI10.1002/sim.10156zbMATH Open1545.62394MaRDI QIDQ6618408

Jacky C. Kuo, David R. Lairson, Wenyaw Chan, Luis G. León Novelo, Armand Brown, Kayo Fujimoto

Publication date: 14 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

censoringcontinuous-time Markov chainlongitudinal binary datalatent class analysislatent classification

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Kolmogorov equations for stochastic PDEs.
• Estimating the dimension of a model
• Generalized network psychometrics: combining network and latent variable models
• Cluster analysis of biomedical image time-series
• Continuous time hidden Markov model for longitudinal data
• KmL: k-means for longitudinal data
• Latent Variable Regression for Multiple Discrete Outcomes
• Latent Class Analysis of Complex Sample Survey Data
• The Matrix Exponential
• A Limited Memory Algorithm for Bound Constrained Optimization
• Comparing Two-Stage Segmentation Methods for Choice Data with a One-Stage Latent Class Choice Analysis
• A continuous-time Markov chain approach with the analytic likelihood in studies of behavioral changes
• Model-based Clustering of Sequential Data with an Application to Contraceptive Use Dynamics
• Estimation in the Mixture of Markov Chains Moving With Different Speeds
• Spatially informed Bayesian neural network for neurodegenerative diseases classification

This page was built for publication: Latent classification model for censored longitudinal binary outcome