run_crt2_design {crt2power}

Find study design output specifications based on all five CRT co-primary design methods.

Description

Allows user to calculate either statistical power, number of clusters per treatment group (K), or cluster size (m), given a set of input values for all five study design approaches.

Usage

run_crt2_design(
  output,
  power = NA,
  K = NA,
  m = NA,
  alpha = 0.05,
  beta1,
  beta2,
  varY1,
  varY2,
  rho01,
  rho02,
  rho1,
  rho2,
  r = 1
)

Arguments

output

Parameter to calculate, either "power", "K", or "m"; character.

power

Desired statistical power; numeric.

K

Number of clusters in each arm; numeric.

m

Individuals per cluster; numeric.

alpha

Type I error rate; numeric.

beta1

Effect size for the first outcome; numeric.

beta2

Effect size for the second outcome; numeric.

varY1

Total variance for the first outcome; numeric.

varY2

Total variance for the second outcome; numeric.

rho01

Correlation of the first outcome for two different individuals in the same cluster; numeric.

rho02

Correlation of the second outcome for two different individuals in the same cluster; numeric.

rho1

Correlation between the first and second outcomes for two individuals in the same cluster; numeric.

rho2

Correlation between the first and second outcomes for the same individual; numeric.

r

Treatment allocation ratio - K2 = rK1 where K1 is number of clusters in experimental group; numeric.

Value

A data frame of numerical values.

Examples

run_crt2_design(output = "power", K = 15, m = 300, alpha = 0.05,
beta1 = 0.1, beta2 = 0.1, varY1 = 0.23, varY2 = 0.25,
rho01 = 0.025, rho02 = 0.025, rho1 = 0.01, rho2  = 0.05)