📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
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Updated
Jul 31, 2024 - R
📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
R package for fitting joint models to time-to-event data and multivariate longitudinal data
Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat
Latent Class Trajectory Models: An R Package
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 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.
R-package for relational event models (one- and two-mode networks)
R package for fitting joint models to time-to-event and longitudinal data
Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood
R/medltmle: Estimation and Inference for Natural Mediation Effect in Longitudinal Data
Broken Stick Model for Irregular Longitudinal Data
optic: Simulation Tool for Causal Inference Using Longitudinal Data
Raw files for a document simulating models for longitudinal data (mixed models and growth curve models).
`MeTEor` is an R Shiny application that offers the possibility to explore longitudinal metabolomics data. For this purpose, a variety of statistical analysis and visualization methods are implemented in MeTEor to help the user to get a quick overview of the data.
This package fits a latent class CTMC model to cluster longitudinal multistate data
Clustering longitudinal data with potential sparse, irregular observations, multiple outcomes, and unbalanced cluster sizes
Implementation of Gaussian Process Panel Modeling in R
Functions for the STARTS Model.
A Shiny interface for the MicrobiomeStat R package, designed to facilitate analysis and visualization of microbiome data.
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