What is the Clinical Trials biostatistics skill?

It is a specialized capability for Claude Code that provides standardized R code patterns and best practices for clinical trial design, randomization, and statistical analysis.

Does this skill support survival analysis?

Yes, it includes methods for survival endpoint sample size calculation using packages like gsDesign and rpact, as well as hazard ratio modeling.

Which randomization methods are covered?

It covers simple randomization, stratified block randomization, and minimization techniques using the blockrand and Minirand packages.

Is the code provided regulatory compliant?

The skill follows ICH E9 guidelines and utilizes industry-standard R packages like mmrm, gMCP, and rbmi, which are widely accepted in the pharmaceutical industry for regulatory submissions.

Clinical Trials Biostatistics

Name: Clinical Trials Biostatistics
Author: choxos

bychoxos

0•

Data Science & ML

Implements industry-standard clinical trial design and statistical analysis workflows using regulatory-compliant R packages.

This skill provides a comprehensive biostatistical toolkit for clinical trial professionals using R. It offers specialized guidance for critical trial phases, including power analysis and sample size calculation for various endpoints, advanced randomization techniques like minimization and stratified blocks, and group sequential designs with complex alpha spending functions. It also facilitates regulatory-compliant analysis through multiplicity adjustments, MMRM for missing data, and ICH E9 estimands framework implementation, making it an essential companion for creating reproducible, high-quality clinical study reports.

Key Features

01Regulatory-compliant multiplicity adjustments and graphical hypothesis testing

020 GitHub stars

03Robust missing data handling with MMRM and reference-based multiple imputation

04Implementation of Group Sequential Designs (GSD) and alpha spending functions

05Automated sample size calculation for t-tests, proportions, and survival endpoints

06Advanced randomization schemes including stratified block and minimization methods

Use Cases

01Developing randomization lists and CONSORT diagrams for multi-center trials

02Designing Phase II/III clinical trials with complex interim analysis stopping rules

03Conducting regulatory-grade statistical analysis for clinical study reports (CSR)

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add choxos/biostatagent clinical-trials

For use in Claude.ai and ChatGPT

Key Features

01Regulatory-compliant multiplicity adjustments and graphical hypothesis testing

020 GitHub stars

03Robust missing data handling with MMRM and reference-based multiple imputation

04Implementation of Group Sequential Designs (GSD) and alpha spending functions

05Automated sample size calculation for t-tests, proportions, and survival endpoints

06Advanced randomization schemes including stratified block and minimization methods

Use Cases

01Developing randomization lists and CONSORT diagrams for multi-center trials

02Designing Phase II/III clinical trials with complex interim analysis stopping rules

03Conducting regulatory-grade statistical analysis for clinical study reports (CSR)