Designing Cluster-Randomized Trials with Two Continuous Co-Primary Outcomes
Calculate cluster size for a cluster-randomized trial with co-primary ...
Find the non-centrality parameter corresponding to Type I error rate a...
Calculate statistical power for a cluster-randomized trial with co-pri...
Calculate cluster size for a cluster-randomized trial with co-primary ...
Calculate cluster size for a cluster-randomized trial with co-primary ...
Calculate required number of clusters per treatment group for a cluste...
Calculate required number of clusters per treatment group for a cluste...
Calculate required number of clusters per treatment group for a cluste...
Calculate required number of clusters per treatment group for a cluste...
Calculate required number of clusters per treatment group for a cluste...
Calculate cluster size for a cluster-randomized trial with co-primary ...
Calculate cluster size for a cluster-randomized trial with co-primary ...
Calculate statistical power for a cluster-randomized trial with co-pri...
Calculate statistical power for a cluster-randomized trial with co-pri...
Calculate statistical power for a cluster-randomized trial with co-pri...
Calculate statistical power for a cluster-randomized trial with co-pri...
Find study design output specifications based on all five CRT co-prima...
Provides methods for powering cluster-randomized trials with two continuous co-primary outcomes using five key design techniques. Includes functions for calculating required sample size and statistical power. For more details on methodology, see Owen et al. (2025) <doi:10.1002/sim.70015>, Yang et al. (2022) <doi:10.1111/biom.13692>, Pocock et al. (1987) <doi:10.2307/2531989>, Vickerstaff et al. (2019) <doi:10.1186/s12874-019-0754-4>, and Li et al. (2020) <doi:10.1111/biom.13212>.