View source: R/functions_multiple_normal.R
| posp_normal | R Documentation |
After getting the "go"-decision to go to phase III, i.e. our results of phase II are over the predefined threshold kappa, this function
calculates the probability, that our program is successfull, i.e. that both endpoints show a statistically significant positive treatment effect in phase III.
posp_normal(
kappa,
n2,
alpha,
beta,
Delta1,
Delta2,
sigma1,
sigma2,
in1,
in2,
fixed,
rho,
rsamp
)
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 |
|
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 |
in1 |
amount of information for |
in2 |
amount of information for |
fixed |
choose if true treatment effects are fixed or random, if TRUE |
rho |
correlation between the two endpoints |
rsamp |
sample data set for Monte Carlo integration |
The output of the function posp_normal() is the probability of a successful program, when going to phase III.
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