treatment_effect_size: Treatment Effect Back Calculation

In preference: 2-Stage Preference Trial Design and Analysis

Description

Calculates the treatment effect that can be detected given a desired study power and overall study sample size for the two-stage randomized design

Usage

treatment_effect_size(
  N,
  power,
  sigma2,
  alpha = 0.05,
  theta = 0.5,
  xi = 1,
  nstrata = 1
)

Arguments

N	overall study sample size.
power	desired study power. Should be numeric value between 0 and 1.
sigma2	variance estimate. Should be positive numeric values. If study is stratified, should be vector of within-stratum variances with length equal to the number of strata in the study.
alpha	desired type I error rate.
theta	proportion of patients assigned to choice arm in the initial randomization. Should be numeric value between 0 and 1 (default=0.5).
xi	a numeric vector of the proportion of patients in each stratum. Length of vector should equal the number of strata in the study and sum of vector should be 1. All vector elements should be numeric values between 0 and 1. Default is 1 (i.e. unstratified design).
nstrata	number of strata. Default is 1 (i.e. unstratified design).

Examples

treatment_effect_size(N=300, power=0.9, sigma2=c(1,0.8), xi=c(0.3,0.7), 
                      nstrata=2)

Example output

Attaching package: 'preference'

The following object is masked from 'package:stats':

    power

[1] 0.4908872

preference documentation built on Sept. 13, 2020, 5:08 p.m.