calc_K_single_1dftest {crt2power} | R Documentation |
Calculate required number of clusters per treatment group for a cluster-randomized trial with co-primary endpoints using the single 1-DF combined test approach.
Description
Allows user to calculate the number of clusters per treatment arm of a cluster-randomized trial with two co-primary endpoints given a set of study design input values, including the statistical power, and cluster size. Uses the single 1-DF combined test approach for clustered data and two outcomes.
Usage
calc_K_single_1dftest(
power,
m,
alpha = 0.05,
beta1,
beta2,
varY1,
varY2,
rho01,
rho02,
rho1,
rho2,
r = 1
)
Arguments
power |
Desired statistical power in decimal form; numeric. |
m |
Individuals per cluster; numeric. |
alpha |
Type I error rate; numeric. |
beta1 |
Effect size for the first outcome; numeric. |
beta2 |
Effect size for the second outcome; numeric. |
varY1 |
Total variance for the first outcome; numeric. |
varY2 |
Total variance for the second outcome; numeric. |
rho01 |
Correlation of the first outcome for two different individuals in the same cluster; numeric. |
rho02 |
Correlation of the second outcome for two different individuals in the same cluster; numeric. |
rho1 |
Correlation between the first and second outcomes for two individuals in the same cluster; numeric. |
rho2 |
Correlation between the first and second outcomes for the same individual; numeric. |
r |
Treatment allocation ratio - K2 = rK1 where K1 is number of clusters in experimental group; numeric. |
Value
A data frame of numerical values.
Examples
calc_K_single_1dftest(power = 0.8, m = 300, alpha = 0.05,
beta1 = 0.1, beta2 = 0.1, varY1 = 0.23, varY2 = 0.25,
rho01 = 0.025, rho02 = 0.025, rho1 = 0.01, rho2 = 0.05)