Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effects
Generate optimal design parameters using ant colony optimization
Optimal sample allocation calculation for single-level randomized cont...
Optimal sample allocation calculation for single-level experiments det...
Optimal sample allocation calculation for two-level CRTs probing media...
Optimal sample allocation calculation for two-level CRTs probing moder...
Optimal sample allocation calculation for two-level CRTs detecting mai...
Optimal sample allocation calculation for two-level multisite-randomiz...
Optimal sample allocation identification for two-level multisite rando...
Optimal sample allocation calculation for two-level MRTs detecting mai...
Optimal sample allocation calculation for three-level CRTs detecting m...
Optimal sample allocation calculation for three-level MRTs detecting m...
Optimal sample allocation calculation for four-level CRTs detecting ma...
Optimal sample allocation calculation for four-level MRTs detecting ma...
Optimal Design and Statistical Power for Experimental Studies Investig...
Budget and/or sample size, power, MDES calculation for MRTs investigat...
Budget and/or sample size, power, MDES calculation for single-level ex...
Budget and/or sample size, power calculation for CRTs probing mediatio...
Budget and/or sample size, power, MDES calculation for two-level CRTs ...
Budget and/or sample size, power, MDES calculation for MRTs investigat...
Budget and/or sample size, power, MDES calculation for two-level MRTs ...
Budget and/or sample size, power, MDES calculation for two-level MRTs ...
Budget and/or sample size, power, MDES calculation for three-level CRT...
Budget and/or sample size, power, MDES calculation for three-level MRT...
Budget and/or sample size, power, MDES calculation for four-level CRTs...
Budget and/or sample size, power, MDES calculation for four-level MRTs...
Relative efficiency (RE) calculation
Relative precision and efficiency (RPE) calculation
Calculate the optimal sample size allocation that uses the minimum resources to achieve targeted statistical power in experiments. Perform power analyses with and without accommodating costs and budget. The designs cover single-level and multilevel experiments detecting main, mediation, and moderation effects (and some combinations). The references for the proposed methods include: (1) Shen, Z., & Kelcey, B. (2020). Optimal sample allocation under unequal costs in cluster-randomized trials. Journal of Educational and Behavioral Statistics, 45(4): 446-474. <doi:10.3102/1076998620912418>. (2) Shen, Z., & Kelcey, B. (2022b). Optimal sample allocation for three-level multisite cluster-randomized trials. Journal of Research on Educational Effectiveness, 15 (1), 130-150. <doi:10.1080/19345747.2021.1953200>. (3) Shen, Z., & Kelcey, B. (2022a). Optimal sample allocation in multisite randomized trials. The Journal of Experimental Education, 90(3), 693-711. <doi:10.1080/00220973.2020.1830361>. (4) Shen, Z., Leite, W., Zhang, H., Quan, J., & Kuang, H. (2025). Using ant colony optimization to identify optimal sample allocations in cluster-randomized trials. The Journal of Experimental Education, 93(1), 167-185. <doi:10.1080/00220973.2024.2306392>. (5) Shen, Z., Li, W., & Leite, W. (in press). Statistical power and optimal design for randomized controlled trials investigating mediation effects. Psychological Methods. <doi:10.1037/met0000698>. (6) Champely, S. (2020). pwr: Basic functions for power analysis (Version 1.3-0) [Software]. Available from <https://CRAN.R-project.org/package=pwr>.