Repository navigation
longitudinal-data
- Website
- Wikipedia
DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
An R package for Simulation Investigation for Empirical Network Analysis
powerlmm R package for power calculations for two- and three-level longitudinal multilevel/linear mixed models.
Shiny App for Repeated Measurements Course
📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
☂️ 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
[CVPR'25] Enhanced Contrastive Learning with Multi-view Longitudinal Data for Chest X-ray Report Generation
Multiple Frequency Estimation Under Local Differential Privacy in Python
Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat
Latent Class Trajectory Models: An R Package
Online supplementary materials of “Three extensions of the random intercept cross-lagged panel model” by Mulder and Hamaker (2021).
An R package for clustering longitudinal datasets in a standardized way, providing interfaces to various R packages for longitudinal clustering, and facilitating the rapid implementation and evaluation of new methods
R package for fitting joint models to time-to-event data and multivariate longitudinal data
R package for fitting joint models to time-to-event data and multivariate longitudinal data
R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.
The University of Pittsburgh English Language Institute Corpus (PELIC) dataset
The University of Pittsburgh English Language Institute Corpus (PELIC) dataset
Gaussian process regression + automatical model selection for logitudinal -omics data
Sequence-to-sequence image and contour prediction library for longitudinal datasets [PMB'23]