Compute the power of a simple cluster randomized trial with a binary outcome, or determine parameters to obtain a target power.
crtpwr.2prop(alpha = 0.05, power = 0.8, m = NA, n = NA, cv = 0,
p1 = NA, p2 = NA, icc = NA, pooled = FALSE, p1inc = TRUE,
tol = .Machine$double.eps^0.25)The level of significance of the test, the probability of a Type I error.
The power of the test, 1 minus the probability of a Type II error.
The number of clusters per condition. It must be greater than 1.
The mean of the cluster sizes.
The coefficient of variation of the cluster sizes. When cv = 0,
the clusters all have the same size.
The expected proportion in the treatment group.
The proportion in the control group.
The intraclass correlation.
Logical indicating if pooled standard error should be used.
Logical indicating if p1 is expected to be greater than p2.
Numerical tolerance used in root finding. The default provides at least four significant digits.
The computed argument. #' @examples # Find the number of clusters per condition needed for a trial with alpha = .05, # power = 0.8, 10 observations per cluster, no variation in cluster size, probability in condition 1 of .1 and condition 2 of .2, and icc = 0.1. crtpwr.2prop(n=10 ,p1=.1, p2=.2, icc=.1) # # The result, showimg m of greater than 37, suggests 38 clusters per condition should be used.
Jonathan Moyer (jon.moyer@gmail.com)