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power-optimization-patterns

Direct and tradeoff-based optimization strategies for clinical trial design. Use when optimizing sample size, selecting design parameters, or performing sensitivity analysis.

5estrelas
Atualizado há 5 meses

Ver no GitHub ↗ Licença: MIT

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Power Optimization Patterns

When to Use This Skill

  • Optimizing sample size for target power
  • Selecting design parameters (randomization ratio, event count)
  • Trading off between competing objectives
  • Performing sensitivity analysis
  • Finding optimal regions across scenarios

Clinical Trial Optimization Framework

Problem Formulation

Components:

  • Data Model D(θ): Parameterized by θ (treatment effects, rates, etc.)
  • Analysis Model A(λ): Parameterized by λ (sample size, even

[Description truncada. Veja o README completo no GitHub.]

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