TRAJ2

The Group-Based Trajectory Modeling repository, developed by Community Health and Aging Outcomes (CHAO) Lab – Institute for Health, Health Care Policy & Aging Research – Rutgers, The State University of New Jersey, focuses on identifying and analyzing latent trajectory groups in longitudinal data for two distinct outcomes. This code enables researchers to understand individual and joint trajectories, uncover patterns, and assess dependencies between multiple outcomes. The project includes single-outcome trajectory models, a multi-trajectory model, and visualization tools for comprehensive analysis of longitudinal health data. Purpose: To implement a SAS native macro for group-based trajectory modeling with longitudinal data using NLMIXED procedure as an alternative to Bobby Jones’ PROC TRAJ (using dynamic link libraries written in C). Outputs: 1. Single-Outcome Model: Fits separate trajectory models for two continuous outcomes over multiple time points using a maximum likelihood estimation approach. 2. Multi-Trajectory Model: Combines the two single-outcome models into a unified model to analyze joint trajectories, capturing dependencies between the outcomes. 3. Visualization: Generates visualizations comparing observed vs. predicted trajectories for latent classes and provides averaged posterior probabilities for class membership.