graemeleehickey

joineRML

R package for fitting joint models to time-to-event data and multivariate longitudinal data

joineR

R package for fitting joint models to time-to-event and longitudinal data

comprisk

Comparison of joint models for competing risks and longitudinal data

goldilocks

Implement Goldilocks Bayesian adaptive design for time-to-event outcomes using a piecewise exponential distribution.

adaptDiag

Implement Bayesian adaptive design for diagnostic test clinical trials.

ClinicalTrialSimulation

This repo consists of all the R code examples for the simulating adaptive clinical trials YouTube series by J. Kyle Wathen at

website

Personal website

bayesDP

Tools for the Bayesian Discount Prior Function

BuyseTest

Generalized Pairwise Comparisons

cWR

davis

Data from Davis (2002)

epi2014

Spatial and Temporal Statistical Modelling for Population Health Sciences

FLHR627

Biostatistics PGR Development Course FLHR 627

hosmer-lemeshow

Data from Hosmer & Lemeshow (1999, 2008)

intro-gam-webinar-2020

intro_to_shiny

Introduction to Shiny workshop for satRday conference

jama_intmed_code

This is the code for the figures and calculations contained in the JAMA Int Med article

joint_model

Bayesian joint modeling of longitudinal quality-of-life and survival data

phuse-GT-Package-for-Publication-Quality-Tables-from-R

Talk at phuse Chicago, IL SDE https://www.phuse.eu/sde20-chicago

psrwe

R-IQ-OQ

R-IQ-OQ is an R/Sweave based program designed to serve as a foundation for the Installation Qualification (IQ) and Operational Qualification (OQ) of R (http://www.r-project.org/) when used in environments (such as regulated clinical trials) where such processes may be required.

RMD-Shiny-session-2020-4-21

RMD Shiny Intro Session by Phil Bowsher & Shannon Hagerty on Tues, Apr 21st, 2020

rwetools

tableman

Data from Tableman and Kim (2003)

tests-as-linear

Common statistical tests are linear models (or: how to teach stats)

tocilizumab_reanalysis

Workshop-R-Tensorflow-Scientific-Computing

Workshop R for Deep Learning with Tensorflow with Applications in Research & Scientific Computing