getSizeMean {GenTwoArmsTrialSize}

General Formulas for Sample Size Calculation

Description

This function computes the sample size required for two arms clinical trials with continuous outcome measure. Four hypothesis tests are available under two allocation designs.

Usage

getSizeMean(
  design = c("parallel", "crossover"),
  test = c("equality", "noninferiority", "superiority", "equivalence"),
  alpha = 0.05,
  beta = 0.2,
  sigma,
  k = 1,
  delta = 0,
  TTE,
  rho = c(0.05, 0.07),
  r = 0.1
)

Arguments

design

allocation method (parallel or crossover).

test

four hypothesis tests: equality, noninferiority, superiority, and equivalence.

alpha

level of significance.

beta

type II error.

sigma

pooled standard deviation of two groups.

k

ratio of control to treatment.

delta

delta margin in test hypothesis.

TTE

target treatment effect or effect size.

rho

vector of length 2, positive noncompliance rates of two arms.

r

projected proportion of trial uniform loss of follow-up.

Value

sample size per arm.

Examples

# Ex 1. (n_trt=91, n_ctl=91)
getSizeMean(design="parallel", test="equality", alpha=0.05, beta=0.20,
  sigma=0.10, k=1, delta=0, TTE=0.05, rho=c(0.05, 0.07), r=0.1)

getSizeMean(design="parallel", test="noninferiority", alpha=0.05,
 beta=0.20, sigma=0.10, k=1, delta=-0.05, TTE=0, rho=c(0.05, 0.07), r=0.1)

# Ex 3. (n_trt=1022, n_ctl=1022)
getSizeMean(design="parallel", test="superiority", alpha=0.05, beta=0.20,
  sigma=0.10, k=1, delta=0.05, TTE=0.07, rho=c(0.05, 0.07), r=0.1)

# Ex 4. (n_trt=113, n_ctl=113)
getSizeMean(design="parallel", test="equivalence", alpha=0.05, beta=0.20,
  sigma=0.10, k=1, delta=0.05, TTE=0.01, rho=c(0.05, 0.07), r=0.1)

# Ex 5. (n_trt=23, n_ctl=23)
getSizeMean(design="crossover", test="equality", alpha=0.05, beta=0.20,
 sigma=0.10, k=1, delta=0, TTE=0.05, rho=c(0.05, 0.07), r=0.1)

# Ex 6. (n_trt=14, n_ctl=14)
getSizeMean(design="crossover", test="noninferiority", alpha=0.05,
 beta=0.20, sigma=0.10, k=1, delta=-0.05, TTE=0, rho=c(0.05, 0.07), r=0.1)

# Ex 7. (n_trt=21, n_ctl=21)
getSizeMean(design="crossover", test="superiority", alpha=0.05, beta=0.20,
 sigma=0.10, k=1, delta=0.05, TTE=0.01, rho=c(0.05, 0.07), r=0.1)

# Ex 8. (n_trt=29, n_ctl=29)
getSizeMean(design="crossover", test="equivalence", alpha=0.05, beta=0.20,
 sigma=0.10, k=1, delta=0.05, TTE=0.01, rho=c(0.05, 0.07), r=0.1)