User guide

This page presents the user guide of Leaspy. Leaspy is a software package for the statistical analysis of longitudinal data, particularly medical data that comes in a form of repeated observations of patients at different time-points.

• 1. Get started
  • 1.1. Installation
  • 1.2. Leaspy in a nutshell
• 2. Mathematical Background
  • 2.1. Nonlinear mixed effect models
    • 2.1.1. Parameter estimation
  • 2.2. Riemannian framework
    • 2.2.1. Disease progression represented as trajectory
    • 2.2.2. Trajectory shape defined by Riemmanian metric
    • 2.2.3. Disentanglement of parameters with a hierarchical model
  • 2.3. References
• 3. Models
  • 3.1. Introduction to Spatio-Temporal Models
    • 3.1.1. Temporal Random Effects
    • 3.1.2. Spatial Random Effects
  • 3.2. Logistic Model
    • 3.2.1. Definition
    • 3.2.2. Data
    • 3.2.3. Mathematical background
  • 3.3. Joint Model
    • 3.3.1. Definition
    • 3.3.2. Data
    • 3.3.3. Mathematical background
  • 3.4. Mixture Model
    • 3.4.1. Definition
    • 3.4.2. Data
    • 3.4.3. Mathematical background
    • 3.4.4. Model summary
  • 3.5. References
• 4. Algorithms
  • 4.1. Fit
    • 4.1.1. Prerequisites
    • 4.1.2. Running Task
    • 4.1.3. Output
  • 4.2. Personalize
  • 4.3. Estimate
  • 4.4. Simulate
    • 4.4.1. Prerequisites
    • 4.4.2. Running the Task
    • 4.4.3. Output
    • 4.4.4. Setting options
  • 4.5. References
• 5. Models Evaluation
  • 5.1. Convergence diagnosis
  • 5.2. Fit metrics
    • 5.2.1. Bayesian Approach
    • 5.2.2. Frequentist Approach
  • 5.3. Prediction metrics
    • 5.3.1. Repeated Measures
    • 5.3.2. Events
  • 5.4. References