Reproducibility Standards

What problem does it solve?

This Skill addresses the challenge of ensuring that R analyses are reproducible, preventing "it works on my machine" issues and enabling seamless collaboration and auditing.

Core Features & Use Cases

• Dependency Management: Uses renv to lock package versions for consistent environments.
• Pipeline Automation: Leverages targets (or drake) to build efficient, reproducible analysis workflows.
• Random Seed Protocol: Establishes clear guidelines for setting and documenting random seeds for stochastic operations.
• Literate Programming: Promotes the use of R Markdown and Quarto for integrated code, text, and output.
• Use Case: When starting a new R project, use this Skill to set up renv for package management and define your analysis pipeline in _targets.R to ensure all future runs produce the same results.

Quick Start

Initialize renv for your project by running renv::init() in your R console.