asremlPlus is an R package that augments the use of 'ASReml-R' and 'ASReml4-R' in fitting mixed models
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Updated
Jun 10, 2024 - R
asremlPlus is an R package that augments the use of 'ASReml-R' and 'ASReml4-R' in fitting mixed models
💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
Extended Joint Models for Longitudinal and Survival Data
CRAN Task View: Mixed, Multilevel, and Hierarchical Models in R
Characterize gene dynamics over trajectories using GLMs, GEEs, & GLMMs.
An R data package for the book "Applied longitudinal data analysis: Modeling change and event occurrence" by Singer and Willett (2003).
Generalised joint models of survival and multivariate longitudinal data
An introduction to the MixedModels.jl ecosystem in Julia
Neuroimaging (EEG, fMRI, pupil ...) regression analysis in Julia
A Julia package for fitting (statistical) mixed-effects models
The book "Embrace Uncertainty: Fitting Mixed-Effects Models with Julia"
Plotting functionality for MixedModels.jl implemented in Makie
Code for the paper: Mixed Models with Multiple Instance Learning
RCall support for MixedModels.jl and lme4
Effect size measures and significance tests
Solves kernel ridge regression within the the mixed model framework. All the estimated components and parameters, e.g. BLUP of dual variables and BLUP of random predictor effects for the linear kernel (also known as RR-BLUP), are available.
Permutation tests for MixedModels.jl
Simulation tools for Mixed Models
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