- 1. Overview and Guidance
- 2. Randomized Controlled Trials (RCTs) in Education and the Problem of Missing Data
- 3. Selected Techniques for Addressing Missing Data in RCT Impact Analysis
- 4. Testing the Performance of Selected Missing Data Methods
- References
- Exhibits
- Appendix A: Missing Data Bias as a Form of Omitted Variable Bias
- Appendix B: Resources for Using Multiple Imputation
- Appendix C: Specifications for Missing Data Simulations
- Appendix D: Full Set of Simulation Results
- Appendix D: Tables
- Appendix E: Standards for Judging the Magnitude of the Bias for Different Missing Data Methods
PDF & Related Info
List of Exhibits
| Exhibit 1 | Numeric Example of Bounding Approach to Estimating Impacts on Dichotomous Outcomes |
| Exhibit 2 | Missing Data Probabilities Under Three Different Scenarios: The Situation in Which the Overall Missing Data Rate = 40% |
| Exhibit 3 | Summary of Simulation Results, Missing Data for 40% of Students |
| Exhibit 4 | Summary of Simulation Results, Missing Data for 40% of Schools |