💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
-
Updated
Dec 25, 2024 - R
💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)
A Julia package for fitting (statistical) mixed-effects models
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 **Superseded by the models-by-example repo**.
Effect size measures and significance tests
An R package for experimental psychologists
Covers the basics of mixed models, mostly using @lme4
Extended Joint Models for Longitudinal and Survival Data
Material for a workshop on Bayesian stats with R
An R package for extracting results from mixed models that are easy to use and viable for presentation.
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
👓 Functions related to R visualizations
GLMMs with adaptive Gaussian quadrature
Formulas for mixed-effects models in Python
Neuroimaging (EEG, fMRI, pupil ...) regression analysis in Julia
Bayesian estimation of the finishing skill of football players
This repository collects various small code snippets or short instructions on how to use or define specific mixed models, mostly with packages lme4 and glmmTMB.
A random-forest-based approach for imputing clustered incomplete data
Add a description, image, and links to the mixed-models topic page so that developers can more easily learn about it.
To associate your repository with the mixed-models topic, visit your repo's landing page and select "manage topics."