Covers the basics of mixed models, mostly using @lme4

A unified framework for data analysis with GLM/GLMM in R

An R Package for Quick Uncertainty Intervals

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

Mixed models @lme4 + custom covariances + parameter constraints

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.

Workshop on using Mixed Models with R

A quick reference for how to run many models in R.

Demonstration of alternatives to lme4

Functions for using mgcv for mixed models. 📈

Implementing a Generalized Linear Mixed Effects Model (GLMM) on a Before-After-Control-Impact (BACI) study design related to coastal dune restoration

Bits of code to help clean up and display statistical analyses, largely in R.

pelatihan-2020-metal

This incomplete repository is used to facilitate the consultation of individual files in this project. Only files smaller than 100 MB are available here. The complete project is available at https://doi.org/10.17605/OSF.IO/GT5UF.

Data and code to Estévez & Takács (2022) 'Brokering or sitting between two chairs? A group perspective on workplace gossip'. Frontiers in Psychology, 13: 815383.

Elevational variation in tropical trees analysis

Applied Regression In R

Visualise the output from allFit(), to look at the parameters for a set of predictors across a set of optimizers (e.g., bobyqa, Nelder-Mead, etc.)

R package for computing, extracting, and visualizing response-contingencies

Data analysis for a water inundation experiment on dipterocarps...