crtpwr.2prop: Power calculations for simple cluster randomized trials,...

Description Usage Arguments Value Authors

View source: R/crtpwr.2prop.R

Description

Compute the power of a simple cluster randomized trial with a binary outcome, or determine parameters to obtain a target power.

Usage

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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)

Arguments

alpha

The level of significance of the test, the probability of a Type I error.

power

The power of the test, 1 minus the probability of a Type II error.

m

The number of clusters per condition. It must be greater than 1.

n

The mean of the cluster sizes.

cv

The coefficient of variation of the cluster sizes. When cv = 0, the clusters all have the same size.

p1

The expected proportion in the treatment group.

p2

The proportion in the control group.

icc

The intraclass correlation.

pooled

Logical indicating if pooled standard error should be used.

p1inc

Logical indicating if p1 is expected to be greater than p2.

tol

Numerical tolerance used in root finding. The default provides at least four significant digits.

Value

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.

Authors

Jonathan Moyer ([email protected])


clusterPower documentation built on Sept. 5, 2017, 9:06 a.m.