tidy-itc-workflowlisted

# Tidy ITC Workflow Apply tidy modelling principles from "Tidy Modeling with R" (TMwR) to indirect treatment comparison analyses for consistent, reproducible, and maintainable code. ## When to Use This Skill - Setting up a new ITC analysis project - Building reproducible analysis pipelines - Creating standardized interfaces across ITC methods - Ensuring code quality and maintainability - Reviewing code for tidy modelling compliance ## Core Principles from TMwR ### 1. The "Pit of Success" Philosophy - Software should facilitate proper usage by design - Users should "fall into winning practices" naturally - Interface must protect users from methodological errors ### 2. Workflow-Centric Architecture Every ITC analysis follows this structure: ``` Data → Validation → Preparation → Analysis → Diagnostics → Reporting ``` ### 3. Consistent Interfaces All ITC functions should have predictable patterns: ```r # Standard function signature pattern itc_function( data, # Primary data input outcome_var, # Outcome variable name treatment_var, # Treatment variable name covariates = NULL, # Optional covariates method = "default", # Method specification alpha = 0.05, # Significance level seed = NULL, # For reproducibility verbose = TRUE, # Progress messages ... # Additional method-specific args ) # Standard return structure list( results = tibble(...), # Main resul