interim_postpred {baskexact}  R Documentation 
Interim analysis based on the posterior predictive probability
Description
Conducts an interim analysis based on the posterior predictive probability.
Usage
interim_postpred(design, ...)
## S4 method for signature 'TwoStageBasket'
interim_postpred(
design,
n,
n1,
r1,
lambda,
weight_mat,
globalweight_fun = NULL,
globalweight_params,
prob_futstop = 0.1,
prob_effstop = 0.9,
...
)
Arguments
design 
An object of class 
... 
Further arguments. 
n 
The sample size per basket. 
n1 
The sample size per basket for the interim analysis in case of a twostage design. 
r1 
Vector of responses after the interim analysis. 
lambda 
The posterior probability threshold. See details for more information. 
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_postpred
conducts an interim analysis with possible
stop for efficacy and futility based on the posterior predictive probability.
If the posterior predictive probability is less than prob_fustop
the
basket is stopped for futility, if the posterior predictive 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_postpred(TwoStageBasket)
: Interim analysis based on the posterior predictive probabilty for twostage basket designs.
Examples
design < setupTwoStageBasket(k = 3, p0 = 0.2)
toer(design, n = 20, n1 = 10, lambda = 0.99, interim_fun = interim_postpred,
weight_fun = weights_fujikawa)