This project, A Statistical Framework and Tools for Planning Multilevel Randomized Cost-Effectiveness Trials, develops methods and software for planning education and social-program evaluations that combine impact evidence with cost evidence.
Within the lab, this project is the main home for methods, software, and dissemination on cost-effectiveness trial planning. It links impact evaluation with cost evidence so that study design can support education decision-making.
Project Information
- Funding agency: National Science Foundation
- Award ID: DRL-2000705
- Role: Co-Principal Investigator and University of Florida Campus PI
- PI/Co-PIs: Nianbo Dong, Rebecca Maynard, Ben Kelcey, Jessaca Spybrook, Wei Li
- Project period: September 1, 2020-August 31, 2023; no-cost extension through August 31, 2026
- Award amount: $1,274,904
- UF subcontract: $211,051
Project Focus
- Develop statistical tools for planning multilevel randomized cost-effectiveness trials.
- Support power and sample-size planning when outcomes, impacts, and costs are jointly considered.
- Produce software and guidance for researchers designing education and social-program evaluations.
Related Publications
- Li, W., Dong, N., Maynard, R., Kelcey, B., Spybrook, J., & Xu, Y. (2025). Sample size planning in the design of two-level randomized cost-effectiveness trials. Research on Social Work Practice, 35(3), 307-320. doi:10.1177/10497315241281501
- Dong, N., Maynard, R., Kelcey, B., Spybrook, J., Li, W., & Bowden, B. (2025). Advantages of Monte Carlo confidence intervals for incremental cost-effectiveness ratios: A comparison of five methods. Journal of Research on Educational Effectiveness, 18(4), 951-979. doi:10.1080/19345747.2024.2393412
- Li, W., Dong, N., Maynard, R., Spybrook, J., & Kelcey, B. (2023). Experimental design and statistical power for cluster randomized cost-effectiveness trials. Journal of Research on Educational Effectiveness, 16(4), 681-706. doi:10.1080/19345747.2022.2142177
- Li, W., Dong, N., & Maynard, R. (2020). Power analysis for two-level multisite randomized cost-effectiveness trials. Journal of Educational and Behavioral Statistics, 45(6), 690-718. doi:10.3102/1076998620911916
Related Software
- Li, W., Dong, N., Maynard, R. A., Spybrook, J., & Kelcey, B. (2023). PowerUp!-CEA: A tool for calculating statistical power in multilevel randomized cost-effectiveness trials (Version 1.2). Resources.
Related Presentations
- Dong, N., Li, W., & Kelcey, B. (2025). Statistical power for incremental cost-effectiveness ratios: A Monte Carlo confidence interval approach. SREE Annual Meeting.
- Dong, N., Li, W., & Kelcey, B. (2025). Statistical power for incremental cost-effectiveness ratios based on Monte Carlo intervals in multisite randomized trials. AERA Annual Meeting.
- Dong, N., Maynard, R., Li, W., Kelcey, B., & Qiu, P. (2024). Methods and tools for comparing and interpreting incremental cost-effectiveness ratios. SREE Annual Meeting.
- Li, W., Dong, N., Maynard, R., Kelcey, B., Spybrook, J., & Xu, Y. (2024). Power analysis for multisite randomized cost-effectiveness trials with site fixed effects. AERA Annual Meeting.
Related Projects
- Binary Outcomes in Multilevel Cost-Effectiveness Trials
- Scaling Targeted Reading Instruction
- Florida Embedded Practices and Intervention with Caregivers
- Tools for Families
NSF Acknowledgment and Disclaimer
This material is based upon work supported by the National Science Foundation under Award No. DRL-2000705. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.