mixed-models
There are 4 repositories under mixed-models topic.
- performance
easystats / performance
:muscle: Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
Language:R 1112 JuliaStats / MixedModels.jl
A Julia package for fitting (statistical) mixed-effects models
Language:Julia 436- Language:Python 211
- Miscellaneous-R-Code
m-clark / Miscellaneous-R-Code
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
Language:R 196 strengejacke / sjstats
Effect size measures and significance tests
Language:R 192neuropsychology / psycho.R
An R package for experimental psychologists
Language:R 152Covers the basics of mixed models, mostly using @lme4
Language:R 144drizopoulos / JMbayes2
Extended Joint Models for Longitudinal and Survival Data
Language:R 94oliviergimenez / bayesian-stats-with-R
Material for a workshop on Bayesian stats with R
Language:HTML 74- models-by-example
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
Language:R 72 An R package for extracting results from mixed models that are easy to use and viable for presentation.
Language:R 70- Language:R 64
unfoldtoolbox / Unfold.jl
Neuroimaging (EEG, fMRI, pupil ...) regression analysis in Julia
Language:Julia 64- Language:Python 63
GLMMs with adaptive Gaussian quadrature
Language:R 63- Language:R 51
huffyhenry / statsbomb-bayesian-shooting
Bayesian estimation of the finishing skill of football players
Language:R 40This repository collects various small code snippets or short instructions on how to use or define specific mixed models, mostly with packages lme4 and glmmTMB.
Language:R 37- Language:R 36
cran-task-views / MixedModels
CRAN Task View: Mixed, Multilevel, and Hierarchical Models in R
Language:R 28- Metida.jl
PharmCat / Metida.jl
Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.
Language:Julia 28 A workshop on using generalized additive models and the mgcv package.
Language:R 27- Language:Julia 27
Mouse-Imaging-Centre / RMINC
Statistics for MINC volumes: A library to integrate voxel-based statistics for MINC volumes into the R environment. Supports getting and writing of MINC volumes, running voxel-wise linear models, correlations, etc.; correcting for multiple comparisons using the False Discovery Rate, and more. With contributions from Jason Lerch, Chris Hammill, Jim Nikelski and Matthijs van Eede. Some additional information can be found here:
Language:R 25Workshop on using Mixed Models with R
Language:R 24- Language:Python 24
- glmmSeq
myles-lewis / glmmSeq
Gene-level general linear mixed model
Language:R 23 JuliaMixedModels / EmbraceUncertainty
The book "Embrace Uncertainty: Fitting Mixed-Effects Models with Julia"
Language:TeX 22- Language:Jupyter Notebook 21
kdzimm / PseudoreplicationPaper
Code used to carry out parameter estimation, correlation estimation, type 1 error analysis, and power analysis for our "Pseudoreplication in Single-Cell" study
Language:HTML 21briencj / asremlPlus
asremlPlus is an R package that augments the use of 'ASReml-R' and 'ASReml4-R' in fitting mixed models
Language:R 19matsueushi / kubo_analysis_julia
「データ解析のための統計モデリング入門」のJulia版Jupyter Notebook
Language:Jupyter Notebook 19RePsychLing / MixedModelsSim.jl
Simulation tools for Mixed Models
Language:Julia 19- Language:R 18
- Language:R 17
- MMFAIR
SchmidtPaul / MMFAIR
:chart_with_upwards_trend::seedling: Mixed Models for Agriculture in R
Language:HTML 17
