pgo_multiple_normal {drugdevelopR} | R Documentation |
Probability to go to phase III for multiple endpoints with normally distributed outcomes
Description
This function calculated the probability that we go to phase III, i.e. that results of phase II are promising enough to get a successful drug development program. Successful means that both endpoints show a statistically significant positive treatment effect in phase III.
Usage
pgo_multiple_normal(
kappa,
n2,
Delta1,
Delta2,
in1,
in2,
sigma1,
sigma2,
fixed,
rho,
rsamp
)
Arguments
kappa |
threshold value for the go/no-go decision rule; vector for both endpoints |
n2 |
total sample size for phase II; must be even number |
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 |
in1 |
amount of information for Delta1 in terms of sample size |
in2 |
amount of information for Delta2 in terms of sample size |
sigma1 |
standard deviation of first endpoint |
sigma2 |
standard deviation of second endpoint |
fixed |
choose if true treatment effects are fixed or random, if TRUE 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 pgo_multiple_normal()
is the probability to go to phase III.