Related Experiment Video
Updated: Jun 3, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
Published on: July 22, 2025
Joint model with latent state for longitudinal and multistate data
E Dantan1, P Joly, J-F Dartigues
1Institut National de la Santé et de la Recherche Médicale, U897, Bordeaux, F-33000, France.
Abstract:
In many chronic diseases, the patient's health status is followed up by quantitative markers. The evolution is often characterized by a 2-phase degradation process, that is, a normal phase followed by a pathological degradation phase preceding the disease diagnosis. We propose a joint multistate model with latent state for the joint modeling of repeated measures of a quantitative marker, time-to-illness and time-to-death. Using data from the PAQUID cohort on cognitive aging, we jointly studied cognitive decline, dementia risk, and death risk. We estimated the mean evolution of cognitive scores given age at dementia for subjects alive and demented, the mean evolution of cognitive scores for subjects alive and nondemented, in addition to age at acceleration of cognitive decline and duration of the pre-dementia phase.
Related Concept Videos
Multicompartment Models: Overview
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
State Space Representation
Consider an RLC circuit, a...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Model Approaches for Pharmacokinetic Data: Compartment Models
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Longitudinal Studies