Shiny App for Repeated Measurements Course

☂️ 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

☂️ 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

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

Trajpy - empowering feature engineering for trajectory analysis across domains.

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

An R-based workflow for conducting repeated measures ANOVA using the ez package, with data wrangling via tidyverse and visualization through ggplot2. Includes data import, transformation to long format, statistical analysis, and graphical summary.

An R-based workflow for conducting repeated measures ANOVA using the ez package, with data wrangling via tidyverse and visualization through ggplot2. Includes data import, transformation to long format, statistical analysis, and graphical summary.