View source: R/functions_multiple_normal.R
pgo_multiple_normal | R Documentation |
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.
pgo_multiple_normal(
kappa,
n2,
Delta1,
Delta2,
in1,
in2,
sigma1,
sigma2,
fixed,
rho,
rsamp
)
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 |
The output of the function pgo_multiple_normal()
is the probability to go to phase III.
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