drugdevelopR (version 1.0.2)

Epgo_bias_normal: Expected probability to go to phase III for bias adjustment programs with normally distributed outcomes

Description

In the case we do not only want do discount for overoptimistic results in phase II when calculating the sample size in phase III, but also when deciding whether to go to phase III or not the functions Epgo_normal_L2 and Epgo_normal_R2 are necessary. The function Epgo_normal_L2 uses an additive adjustment parameter (i.e. adjust the lower bound of the one-sided confidence interval), the function Epgo_normal_R2 uses a multiplicative adjustment parameter (i.e. use estimate with a retention factor)

Usage

Epgo_normal_L2(kappa, n2, Adj, w, Delta1, Delta2, in1, in2, a, b, fixed)
Epgo_normal_R2(kappa, n2, Adj, w, Delta1, Delta2, in1, in2, a, b, fixed)

Value

The output of the functions Epgo_normal_L2 and Epgo_normal_R2 is the expected number of participants in phase III with conservative decision rule and sample size calculation.

Arguments

kappa

threshold value for the go/no-go decision rule

n2

total sample size for phase II; must be even number

Adj

adjustment parameter

w

weight for mixture prior distribution

Delta1

assumed true treatment effect for standardized difference in means

Delta2

assumed true treatment effect for standardized difference in means

in1

amount of information for Delta1 in terms of sample size

in2

amount of information for Delta2 in terms of sample size

a

lower boundary for the truncation

b

upper boundary for the truncation

fixed

choose if true treatment effects are fixed or random, if TRUE Delta1 is used as fixed effect

Examples

res <- Epgo_normal_L2(kappa = 0.1, n2 = 50, Adj = 0, w = 0.3,
                               Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600, 
                               a = 0.25, b = 0.75, fixed = FALSE)
          res <- Epgo_normal_R2(kappa = 0.1, n2 = 50, Adj = 1, w = 0.3,
                               Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600, 
                               a = 0.25, b = 0.75, fixed = FALSE)