adjust_lambda {baskexact}  R Documentation 
Adjust Lambda
Description
Finds the value for lambda
such that the family wise error
rate is protected at level alpha
.
Usage
adjust_lambda(design, ...)
## S4 method for signature 'OneStageBasket'
adjust_lambda(
design,
alpha = 0.025,
p1 = NULL,
n,
weight_fun,
weight_params = list(),
globalweight_fun = NULL,
globalweight_params = list(),
prec_digits,
...
)
## S4 method for signature 'TwoStageBasket'
adjust_lambda(
design,
alpha = 0.025,
p1 = NULL,
n,
n1,
interim_fun,
interim_params = list(),
weight_fun,
weight_params = list(),
globalweight_fun = NULL,
globalweight_params = list(),
prec_digits,
...
)
Arguments
design 
An object of class 
... 
Further arguments. 
alpha 
The onesided signifance level. 
p1 
Probabilities under the alternative hypothesis. If

n 
The sample size per basket. 
weight_fun 
Which function should be used to calculate the pairwise weights. 
weight_params 
A list of tuning parameters specific to

globalweight_fun 
Which function should be used to calculate the global weights. 
globalweight_params 
A list of tuning parameters specific to

prec_digits 
Number of decimal places that are considered when adjusting lambda. 
n1 
The sample size per basket for the interim analysis in case of a twostage design. 
interim_fun 
Which type of interim analysis should be conducted in case of a twostage design. 
interim_params 
A list of tuning parameters specific to

Details
adjust_alpha
finds the greatest value with
prec_digits
for lambda
which controls the family wise error
rate at level alpha
(onesided). A combination of the uniroot
function followed by a grid search is used to finde the correct value
for lambda
.
Value
The greatest value with prec_digits
decimal places for
lambda
which controls the family wise error rate at level
alpha
(onesided) and the exact family wise error rate for this
value of lambda
.
Methods (by class)

adjust_lambda(OneStageBasket)
: Adjust lambda for a singlestage design. 
adjust_lambda(TwoStageBasket)
: Adjust lambda for a twostage design.
Examples
design < setupOneStageBasket(k = 3, shape1 = 1, shape2 = 1, p0 = 0.2)
adjust_lambda(design = design, alpha = 0.025, n = 15,
weight_fun = weights_fujikawa, prec_digits = 4)