Shiny App for Repeated Measurements Course

R package for fitting joint models to time-to-event and longitudinal data

Scikit-longitudinal (Sklong) is an open-source Python library & Scikit-Learn API compliant, tailored to longitudinal machine learning classification tasks. It is ideal for researchers, data scientists, and analysts, as it provides specialist tools for dealing with repeated-measures data challenges

Trajpy - empowering feature engineering for trajectory analysis across domains.

Auto-Scikit-Longitudinal (Auto-Sklong) is an automated machine learning (AutoML) library designed to analyse longitudinal data (Classification tasks focussed as of today) using various search methods. Namely, Bayesian Optimisation via SMAC3, Asynchronous Successive Halving, Evolutionary Algorithms, and Random Search via GAMA

scikit-lexicographical-trees: Based upon Scikit-Learn(-tree), it offers adapted trees and forest for Longitudinal Classification

Computation and visualization of standardized mean differences from simulated data