RCTs 101: The Gold Standard for Impact Evaluation
Why randomization is the most powerful tool for measuring impact
By Aubrey Jolex | February 1, 2025 | 12 min read
Randomized controlled trials (RCTs) are the gold
standard for measuring program impact—but what makes them so powerful? And how do you actually
design and implement one correctly?
Whether you’re evaluating a health intervention, education program, or poverty reduction strategy,
understanding RCTs is essential for rigorous impact evaluation.
What is an RCT?
An RCT is an experimental design where participants are randomly assigned to either a treatment group
(receives the program) or a control group (does not receive the program).
The Key Principle: Randomization
Random assignment ensures that, on average, treatment and control groups are identical except for the
program itself. This means any difference in outcomes can be attributed to the program—not to
pre-existing differences between groups.
Why Randomization Matters
Without randomization, you might compare program participants (who
self-selected or were chosen) to non-participants. But these groups likely differ in motivation,
resources, or other characteristics—making it impossible to isolate the program’s true impact.
The Anatomy of an RCT
1. Baseline Survey
Collect data on participants before program starts
2. Randomization
Randomly assign participants to treatment or control
3. Program Implementation
Deliver the intervention to treatment group only
4. Endline Survey
Measure outcomes for both groups after program
5. Analysis
Compare treatment vs control group outcomes
6. Reporting
Document findings and program impact
Types of Randomization
Individual Randomization
Assign individual people to treatment or control. Best when: intervention is individual-level
(e.g., scholarship, training)
Cluster Randomization
Assign groups (schools, villages, clinics) to treatment or control. Best when: intervention
operates at group level or spillovers are concern
Implementing Randomization with Integrity
Common Threats to Validity
Warning: Compromised Randomization
- Staff changing assignments based on “need”
- Participants swapping between groups
- Selective attrition from one group
Best Practices for Clean Randomization
Centralize Assignment
Use computer-based randomization, not manual selection
Blind When Possible
Keep staff unaware of assignment until after baseline
Lock Assignments
Do not allow changes after randomization
Document Everything
Record randomization procedure and any deviations
Power Analysis: Getting Sample Size Right
A critical step in RCT design is determining how many participants you need. Too few, and you won’t
be able to detect program effects. Too many wastes resources.
Design Your RCT Like a Pro
Use our RCT Field Flow Toolkit to document your research design, intervention
logic, and prepare for randomization.
Centralized study planning hub
Document intervention logic and theory of change
Prepare for power calculations and randomization
Common RCT Design Challenges
Ethical Concerns
Solution: Offer control group the program after study, use lottery for oversubscribed
programs
Spillovers
Solution: Use cluster randomization, ensure sufficient distance between treatment/control
Attrition
Solution: Track participants carefully, over-sample in baseline, analyze differential
attrition
Conclusion
RCTs provide the most credible evidence of program impact when done correctly. Key principles:
RCT Success Checklist
- Conduct proper power analysis
- Implement randomization with integrity
- Collect baseline data before randomization
- Monitor implementation fidelity
- Minimize and track attrition
- Pre-register your analysis plan
Ready to Design Your RCT?
Get the tools and guidance you need
Use Our Toolkit
Comprehensive platform for power analysis, randomization, and complete RCT management.
About the Author
Aubrey Jolex has designed and implemented dozens of RCTs across Asia and Africa with 7+ years of
experience at IFPRI. Learn from real-world experience to implement rigorous evaluations.