danielinteractive's Stars
hakimel/reveal.js
The HTML Presentation Framework
JuliaLang/julia
The Julia Programming Language
TuringLang/Turing.jl
Bayesian inference with probabilistic programming.
RcppCore/RcppEigen
Rcpp integration for the Eigen templated linear algebra library
stefan-m-lenz/JuliaConnectoR
A functionally oriented interface for calling Julia from R
kaskr/RTMB
R bindings to TMB
r-hub/rhub2
The 'R-hub' package builder, v2
insightsengineering/teal.modules.clinical
Provides teal modules for the standard clinical trials outputs
PharmCat/Metida.jl
Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.
rpact-com/rpact
rpact: Confirmatory Adaptive Clinical Trial Design and Analysis
Yu-Group/simChef
An R package to facilitate PCS simulation studies.
Gilead-BioStats/graphicalMCP
Graphical Multiple Comparison Procedures
insightsengineering/hermes
Preprocessing, analyzing, and reporting of RNA-seq data
coolbutuseless/svgpatternsimple
Create some simple repeating SVG patterns in R
openpharma/workshop-r-swe-md
Good Software Engineering Practice for R Packages @ Rockville, MD
PharmCat/ReplicateBE.jl
Mixed model solution for replicate designed bioequivalence study.
mbannick/RobinCar
ROBust INference for Covariate Adjustment in Randomized clinical trials
tye27/RobinCar
Robust inference in covariate-adaptive randomization
dgkf/rpharma-2023-mmrm-workshop
R/Pharma 2023 `mmrm` Workshop
openpharma/savvyr
savvyr: Estimation of adverse event probabilities
Boehringer-Ingelheim/decider
The decider R package: decision making in multiple-arm oncology dose escalation trials with logistic regression
el-meyer/airship
AIRSHIP - An Interactive R-SHIny apP for visualizing tidy long data
openpharma/autoquarto
Utilities for programmatic generation of Quarto output
fpahlke/simulatr
kkmann/simulatr
mjfrigaard/mstsap
Mastering Shiny testServer() application package (demo)
tobiasmuetze/gscounts
cran/nhm
:exclamation: This is a read-only mirror of the CRAN R package repository. nhm — Non-Homogeneous Markov and Hidden Markov Multistate Models
Kong-WayneState/EOSS_MMRM-V1.0
EOSS_MMRM V1.0 is a simulation-based R Shiny app developed for exploring statistical powers and sample sizes required in MMRM trials, allowing early termination and efficacy follow-up.
medianasoft/MCPModPack