interim_posterior {baskexact}  R Documentation 
Interim analysis based on the posterior probability
Description
Conducts an interim analysis based on the posterior probability.
Usage
interim_posterior(design, ...)
## S4 method for signature 'TwoStageBasket'
interim_posterior(
design,
n1,
r1,
weight_mat,
globalweight_fun = NULL,
globalweight_params = list(),
prob_futstop = 0.1,
prob_effstop = 0.9,
...
)
Arguments
design 
An object of class 
... 
Further arguments. 
n1 
The sample size per basket for the interim analysis in case of a twostage design. 
r1 
Vector of responses after the interim analysis. 
weight_mat 
The matrix with all weights. Automatically calculated
in the functions to which 
globalweight_fun 
Which function should be used to calculate the global weights. 
globalweight_params 
A list of tuning parameters specific to

prob_futstop 
Probability cutoff for stopping for futility. 
prob_effstop 
Probability cutoff for stopping for efficacy. 
Details
interim_posterior
conducts an interim analysis with possible
stop for efficacy and futility based on the posterior probability. If the
posterior probability is less than prob_fustop
the basket is stopped
for futility, if the posterior probability is greater than
prob_effstop
the basket is stopped for efficacy. If
prob_fustop = 0
or prob_effstop = 1
then no futilitystop and
no efficacy stop is possible, respectively.
The function is generally not called by the user but passed to another
function such as toer
and pow
to specify which
interim analysis is conducted.
Value
A vector with a length equal to the number of baskets with elements 1, 0 or 1 where 1 means stop for futility, 0 means continuation and 1 means stop for efficacy.
Methods (by class)

interim_posterior(TwoStageBasket)
: Interim analysis based on the posterior probabilty for twostage basket designs.
Examples
design < setupTwoStageBasket(k = 3, p0 = 0.2)
toer(design, n = 20, n1 = 10, lambda = 0.99, weight_fun = weights_fujikawa,
interim_fun = interim_posterior, interim_params = list(prob_futstop = 0.05,
prob_effstop = 0.95))