Covers the basics of mixed models, mostly using @lme4

A document introducing generalized additive models.📈

ggplot-based graphics and useful functions for GAMs fitted using the mgcv package

Mixed models @lme4 + custom covariances + parameter constraints

Testing differences in cell type proportions from single-cell data.

Workshop on using Mixed Models with R

👓 Functions related to R visualizations

Functions for using mgcv for mixed models. 📈

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

Demonstration of alternatives to lme4

An R package for I-prior regression

Stata and R programs to automatically quasi-demean regressors following FGLS-RE or MLE-RE regression

a meta-analysis on the effect of intravenous magnesium on myocardial infarction

Raw files for a document providing an overview of mixed models from varying perspectives.

Cluster-specific logistic regression models for whether an NBA team will make the playoffs given the current statistics of that team. Specifically uses population averaged models (PA) based on generalized estimating equations (GEE); Also, uses cluster-specific (each team) random effects models

Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)

Monte Carlo Simulation comparing the performance of various estimators for panel data with binary dependent variable models

Using Fixed Effect, Random Effect and Hausman Taylor IV to estimate the impacts on wage

Fit band-recovery models with temporal random effects

Pitch Adjusted Swipe Rate Above Average (pSRAA)