cra4: Four-Level Cluster-randomized Trial

In PowerUpR: Power Analysis Tools for Multilevel Randomized Experiments

Description

For main treatment effects, use mdes.cra4() calculate the minimum detectable effect size, power.cra4() to calculate the statistical power, and mrss.cra4() to calculate the minimum required sample size.

Usage

mdes.cra4(power=.80, alpha=.05, two.tailed=TRUE,
          rho2, rho3, rho4, p=.50, r21=0, r22=0, r23=0, r24=0, g4=0,
          n, J, K, L)

power.cra4(es=.25, alpha=.05, two.tailed=TRUE,
           rho2, rho3, rho4, p=.50, r21=0, r22=0, r23=0, r24=0, g4=0,
           n, J, K, L)

mrss.cra4(es=.25, power=.80, alpha=.05, two.tailed=TRUE,
          n, J, K, L0=10, tol=.10,
          rho2, rho3, rho4, p=.50,
          r21=0, r22=0, r23=0, r24=0, g4=0)

Arguments

power	statistical power (1-β).
es	effect size.
alpha	probability of type I error.
two.tailed	logical; TRUE for two-tailed hypothesis testing, FALSE for one-tailed hypothesis testing.
rho2	proportion of variance in the outcome between level 2 units (unconditional ICC2).
rho3	proportion of variance in the outcome between level 3 units (unconditional ICC3).
rho4	proportion of variance in the outcome between level 4 units (unconditional ICC4).
p	proportion of level 4 units randomly assigned to treatment.
g4	number of covariates at level 4.
r21	proportion of level 1 variance in the outcome explained by level 1 covariates.
r22	proportion of level 2 variance in the outcome explained by level 2 covariates.
r23	proportion of level 3 variance in the outcome explained by level 3 covariates.
r24	proportion of level 4 variance in the outcome explained by level 4 covariates.
n	harmonic mean of level 1 units across level 2 units (or simple average).
J	harmonic mean of level 2 units across level 3 units (or simple average).
K	harmonic mean of level 3 units across level 4 units (or simple average).
L	number of level 4 units.
L0	starting value for L.
tol	tolerance to end iterative process for finding L.

Value

fun	function name.
parms	list of parameters used in power calculation.
df	degrees of freedom.
ncp	noncentrality parameter.
power	statistical power (1-β).
mdes	minimum detectable effect size.
L	number of level 4 units.

Examples

# cross-checks
mdes.cra4(rho4=.05, rho3=.05, rho2=.10,
          n=10, J=2, K=3, L=20)
power.cra4(es = .412, rho4=.05, rho3=.05, rho2=.10,
           n=10, J=2, K=3, L=20)
mrss.cra4(es = .412, rho4=.05, rho3=.05, rho2=.10,
          n=10, J=2, K=3)

PowerUpR documentation built on Oct. 25, 2021, 5:06 p.m.