`basksim`

calculates the operating characteristics of different basket trial designs based on simulation.

Install the development veresion with:

With `basksim`

you can calculate the operating characteristics such as rejection probabilities and mean squared error of single-stage basket trials with different designs.

At first, you have to create a design-object using a setup-function. For example to create a design-object for Fujikawaâ€™s design (Fujikawa et al., 2020):

`k`

is the number of baskets, `shape1`

and `shape2`

are the shape parameters of the Beta-prior of the response probabilities of each baskets and `p0`

is the response probability that defines the null hypothesis.

Use `get_details`

to estimate several important operating characteristics:

```
get_details(
design = design,
n = 20,
p1 = c(0.2, 0.5, 0.5),
lambda = 0.95,
epsilon = 1.5,
tau = 0,
iter = 5000
)
# $Rejection_Probabilities
# [1] 0.3448 0.9772 0.9764
#
# $FWER
# [1] 0.3448
#
# $Mean
# [1] 0.2781905 0.4795914 0.4789913
#
# $MSE
# [1] 0.014837404 0.008647713 0.008620234
#
# $Lower_CL
# [1] 0.1395151 0.3341910 0.3336988
#
# $Upper_CL
# [1] 0.4262371 0.6252845 0.6245943
```