worked R examples

GLMMs with adaptive Gaussian quadrature

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.

The book "Embrace Uncertainty: Fitting Mixed-Effects Models with Julia"

code repository for Lagattuta et al. "Repertoire analyses reveal T cell receptor sequence features that influence T cell fate." Nat. Imm. (2022)

Fast cluster-based permutation test for densely-sampled, multi-level time series data (ex: eyetracking, EEG)

General pipeline used for analyzing EEG data where Raw EEG data gets transformed into ERPS and Stats are done in R (Mixed effects models)

GMPE-estimation implements a one-stage estimation algorithm to estimate ground-motion prediction equations (GMPE) with spatial correlation. It also quantifies the uncertainty of spatial correlation and intensity measure predictions.

Steve's Miscellaneous Functions

Generalised Mixed Effects Model. Now any machine learning model can have random effects.

Simple Mixed Effect Models and Censoring

Applying amortizing neural posterior estimation for non-linear mixed effects models

This repository commits to the application of biostatistics knowledge on clinical, randomized trials and observational studies.

Modeling correlated count data

SMLP2024: Advanced methods in frequentist statistics with Julia

Simple mixed-effects growth models applied to tumor growth (modeling the effect of treatment and measurement method)

Life Expectancy Prediction by Country with supervised learning, mixed effect effect modeling, and clustering.

Julia package for fitting regularized linear mixed-effect models on high-dimensional omics data.

R scripts for analysing data from a language production study with bilinguals

Early Growth Genetics Longitudinal Analysis.