overall_power_binom {preference}

Power Calculation from Sample Size

Description

Calculates the study power to detect the preference effect given a particular sample size in a two-stage randomized clinical trial with a binary outcome measure

Usage

overall_power_binom(
  N,
  phi,
  p11,
  p22,
  p1,
  p2,
  alpha = 0.05,
  theta = 0.5,
  xi = 1,
  nstrata = 1
)

Arguments

N

overall study sample size.

phi

the proportion of patients preferring treatment 1. Should be numeric value between 0 and 1. If study is stratified, should be vector with length equal to the number of strata in the study.

p11

response proportion of patients choosing to receive treatment 1 in the choice arm. Should be numeric value between 0 and 1. If study is stratified, should be vector with length equal to the number of strata in the study.

p22

response proportion of patients choosing to receive treatment 2 in the choice arm. Should be numeric value between 0 and 1. If study is stratified, should be vector with length equal to the number of strata in the study.

p1

response proportion of patients randomized to receive treatment 1 in the random arm. Should be numeric value between 0 and 1. If study is stratified, should be vector with length equal to the number of strata in the study.

p2

response proportion of patients randomized to receive treatment 2 in the random arm. Should be numeric value between 0 and 1. If study is stratified, should be vector 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).