EPsProg_multiple_normal: Expected probability of a successful program for multiple...

In Sterniii3/drugdevelopR: Utility-Based Optimal Phase II/III Drug Development Planning

Expected probability of a successful program for multiple endpoints and normally distributed outcomes

Description

This function calculates the probability that our drug development program is successful. Successful is defined as both endpoints showing a statistically significant positive treatment effect in phase III.

Usage

EPsProg_multiple_normal(
  kappa,
  n2,
  alpha,
  beta,
  Delta1,
  Delta2,
  sigma1,
  sigma2,
  step11,
  step12,
  step21,
  step22,
  in1,
  in2,
  fixed,
  rho,
  rsamp
)

Arguments

kappa	threshold value for the go/no-go decision rule;
n2	total sample size for phase II; must be even number
alpha	significance level
beta	1-beta power for calculation of sample size for phase III
Delta1	assumed true treatment effect given as difference in means for endpoint 1
Delta2	assumed true treatment effect given as difference in means for endpoint 2
sigma1	standard deviation of first endpoint
sigma2	standard deviation of second endpoint
step11	lower boundary for effect size for first endpoint
step12	lower boundary for effect size for second endpoint
step21	upper boundary for effect size for first endpoint
step22	upper boundary for effect size for second endpoint
in1	amount of information for Delta1 in terms of sample size
in2	amount of information for Delta2 in terms of sample size
fixed	choose if true treatment effects are fixed or random, if TRUE then Delta1 is used as fixed effect
rho	correlation between the two endpoints
rsamp	sample data set for Monte Carlo integration

Value

The output of the function EPsProg_multiple_normal() is the expected probability of a successfull program, when going to phase III.

Sterniii3/drugdevelopR documentation built on Jan. 26, 2024, 6:17 a.m.