Group-based multi-trajectory modeling
Carnegie Mellon University · University of Pittsburgh Medical Center · +2 more institutions
Abstract
Identifying and monitoring multiple disease biomarkers and other clinically important factors affecting the course of a disease, behavior or health status is of great clinical relevance. Yet conventional statistical practice generally falls far short of taking full advantage of the information available in multivariate longitudinal data for tracking the course of the outcome of interest. We demonstrate a method called multi-trajectory modeling that is designed to overcome this limitation. The method is a generalization of group-based trajectory modeling. Group-based trajectory modeling is designed to identify clusters of individuals who are following similar trajectories of a single indicator of interest such…
Citation impact
- FWCI
- 27.83
- Percentile
- 100%
- References
- 16
Authors
4Topics & keywords
- Trajectory
- Computer science
- Generalization
- Multivariate statistics
- Outcome (game theory)
- Artificial intelligence
- Statistics
- Machine learning
- Good health and well-being