mixed-models

💪 Models' quality and performance metrics (R2, ICC, LOO, AIC, BF, ...)

A Julia package for fitting (statistical) mixed-effects models

Statistical Functions for Regression 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 **Superseded by the models-by-example repo**.

All the convenience of lme4 in python

An R package for experimental psychologists

Covers the basics of mixed models, mostly using @lme4

Material for a workshop on Bayesian stats with R

👓 Functions related to R visualizations

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

GLMMs with adaptive Gaussian quadrature

An R package for extracting results from mixed models that are easy to use and viable for presentation.

Bayesian estimation of the finishing skill of football players

Extended Joint Models for Longitudinal and Survival Data

Formulas for mixed-effects models in Python

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

Notebooks for SMLP2021

A workshop on using generalized additive models and the mgcv package.

Neuroimaging (EEG & fMRI) regression analysis in Julia