irgtt.cont: Power for individually randomized group treatment trial with...

In powertools: Power and Sample Size Tools

Power for individually randomized group treatment trial with continuous outcome

Description

Computes power and sample size for an individually randomized group treatment trial with a continuous outcome, in which after individual randomization, individuals in the intervention/treatment arm are clustered. Can solve for power, J, m, n, delta or alpha.

Usage

irgtt.cont(
  m = NULL,
  J = NULL,
  n = NULL,
  delta = NULL,
  sd = 1,
  icc = 0,
  Theta = 1,
  alpha = 0.05,
  power = NULL,
  sides = 2,
  tol = .Machine$double.eps^0.25,
  v = FALSE
)

Arguments

m	The number of subjects per cluster in the intervention arm.
J	The total number of clusters in the intervention arm.
n	The total number of participants in the control arm.
delta	The difference between the intervention and control means under the alternative minus the difference under the null hypothesis.
sd	The total standard deviation of the outcome variable in the control arm; defaults to 1.
icc	The intraclass correlation coefficient in the treatment arm; defaults to 0.
Theta	The ratio of the total variance in the intervention and control arms; defaults to 1.
alpha	The significance level (type 1 error rate); defaults to 0.05.
power	The specified level of power.
sides	Either 1 or 2 (default) to specify a one- or two-sided hypothesis test.
tol	The desired accuracy (convergence tolerance) for uniroot.
v	Either TRUE for verbose output or FALSE (default) to output computed argument only.

Details

Power is solved for using noncentral t or F distribution; other quantities (for example, sample sizes) are solved for using normal approximation.

Value

A list of the arguments (including the computed one).

Examples

irgtt.cont(m = 10, J = 12, n = 120, delta = 0.4, icc = 0.05, Theta = 1, power = NULL)
irgtt.cont(m = 10, J = 12, n = NULL, delta = 0.4, icc = 0.05, Theta = 1, power = 0.8)

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