re.clustsize.bin: Relative efficiency of a cluster randomized trial with binary...

In powertools: Power and Sample Size Tools

Relative efficiency of a cluster randomized trial with binary outcome with varying cluster sizes

Description

For a binary outcome, computes the relative efficiency (ratio of the variances) of a cluster randomized trial with varying cluster sizes to that of a cluster randomized trial with constant cluster sizes, assuming equal total number of subjects.

Usage

re.clustsize.bin(m, m.sd, pc, pt, sigma.u)

Arguments

m	The number of subjects per cluster or the mean cluster size (if unequal number of participants per cluster).
m.sd	The standard deviation of cluster sizes (in case of unequal number of participants per cluster).
pc	The probability of the outcome in control clusters.
pt	The probability of the outcome in treatment clusters.
sigma.u	Standard deviation of the cluster random effect.

Details

Candel MJJM and van Breukelen GJP (2010) Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression. Statistics in Medicine 29(14):1488-1501.

Value

The computed RE.

Examples

re.clustsize.bin(m = 60, m.sd = 45, pc = 0.25, pt = 0.15, sigma.u = 0.3)

powertools documentation built on April 4, 2025, 5:02 a.m.