experimental-design

name	experimental-design
description	Design rigorous scientific experiments with power analysis and controls. Use when: user needs to plan an experiment, calculate sample sizes, or set up controls. NOT for: running experiments or analyzing collected data.
metadata	{"openclaw":{"emoji":"🔧"}}

Experimental Design Skill

Design rigorous, reproducible experiments across scientific disciplines.

When to Use

• "Design an experiment to test..."
• "How many samples do I need?"
• "What controls should I include?"
• "Help me plan a clinical trial"
• "Is this experimental design valid?"
• Power analysis and sample size calculation

When NOT to Use

• Running the actual experiment (use code-execution)
• Analyzing collected data (use scipy-analysis + statsmodels-stats)
• Writing up results (use paper-writing)
• Literature review (use literature-search)

Design Components

1. Research Question and Hypotheses

• State clear, testable research question
• Formulate H0 and H1 (see hypothesis-gen skill)
• Define primary and secondary outcomes

2. Study Design Selection

Design	When to Use	Strengths	Weaknesses
RCT	Causal inference needed	Gold standard causality	Expensive, ethical limits
Factorial	Multiple factors	Tests interactions	Complex analysis
Crossover	Within-subject comparison	Reduced variability	Carryover effects
Quasi-experimental	Randomization impossible	Practical feasibility	Weaker causality
Observational (cohort)	Long-term outcomes	Natural setting	Confounding
Case-control	Rare outcomes	Efficient for rare events	Recall bias

3. Power Analysis

# Sample size calculation template (using scipy/statsmodels)
from statsmodels.stats.power import TTestIndPower
analysis = TTestIndPower()
n = analysis.solve_power(
    effect_size=0.5,   # Cohen's d (small=0.2, medium=0.5, large=0.8)
    alpha=0.05,         # Significance level
    power=0.80,         # Statistical power (commonly 0.80 or 0.90)
    ratio=1.0,          # Ratio of group sizes (n2/n1)
    alternative='two-sided'
)
print(f"Required sample size per group: {int(n) + 1}")

Key parameters:

• Effect size: Expected magnitude of difference
• Alpha: Type I error rate (usually 0.05)
• Power: 1 - Type II error rate (usually 0.80-0.95)
• Attrition: Add 10-20% for expected dropout

4. Variable Control

• Independent variables: What you manipulate
• Dependent variables: What you measure
• Confounding variables: What could bias results
• Control strategies: Randomization, blocking, matching, blinding

5. Randomization

• Simple randomization (coin flip)
• Block randomization (balanced groups)
• Stratified randomization (balance key covariates)
• Cluster randomization (group-level assignment)

6. Blinding

• Single-blind: Participants unaware of assignment
• Double-blind: Participants and researchers unaware
• Triple-blind: Including data analysts

Reproducibility Checklist

• Protocol pre-registered (OSF, ClinicalTrials.gov, PROSPERO)
• All materials/reagents specified with catalog numbers
• Detailed step-by-step procedure written
• Statistical analysis plan pre-specified
• Data management plan documented
• Raw data sharing plan established
• Code availability ensured
• Sample size justified with power analysis
• Randomization method specified
• Blinding procedures documented
• Inclusion/exclusion criteria defined
• Primary endpoint pre-specified

Output Format

## Experimental Design: [Title]

**Research Question**: [Clear question]
**Design Type**: [RCT/Factorial/etc.]

### Participants/Samples
- Population: [target population]
- Inclusion: [criteria]
- Exclusion: [criteria]
- Sample Size: N=[total] ([n] per group) — Power=[X], alpha=[X], effect=[X]

### Groups
- Experimental: [treatment description]
- Control: [control description]
- Blinding: [single/double/triple/none]

### Variables
- IV: [variables]
- DV: [primary + secondary outcomes]
- Controls: [confounds and how addressed]

### Procedure
1. [Step-by-step protocol]

### Analysis Plan
- Primary: [statistical test]
- Secondary: [additional analyses]
- Multiple comparison correction: [method]

### Timeline
- [Phase 1]: [duration]
- [Phase 2]: [duration]

### Ethics
- IRB/IACUC requirements: [details]
- Consent procedure: [details]