pmax_beta {RARtrials} | R Documentation |
Posterior Probability that a Particular Arm is the Best for Binary Endpoint
Description
Calculate posterior probability that a particular arm is the best in a trial using Bayesian response-adaptive randomization with
a control group (the Thall Wathen method). The conjugate prior distributions follow Beta (
) distributions
for binary outcomes in each arm and can be specified individually.
Usage
pmax_beta(
armn,
a1 = NULL,
b1 = NULL,
a2 = NULL,
b2 = NULL,
a3 = NULL,
b3 = NULL,
a4 = NULL,
b4 = NULL,
a5 = NULL,
b5 = NULL,
side,
...
)
Arguments
armn |
number of arms in the trial with values up to 5. When |
a1 , b1 |
|
a2 , b2 |
|
a3 , b3 |
|
a4 , b4 |
|
a5 , b5 |
|
side |
direction of a one-sided test, with values 'upper' or 'lower'. |
... |
additional arguments to be passed to |
Details
This function calculates the results of formula for
side
equals to 'upper' and the results of formula for
side
equals to 'lower'. This function returns the probability that the posterior probability of arm
is maximal or minimal in trials with up to five arms.
Value
a probability that a particular arm is the best in trials up to five arms.
Examples
pmax_beta(armn=5,a1=8,b1=10,a2=5,b2=19,a3=8,b3=21,
a4=6, b4=35, a5=15, b5=4, side='upper')
pmax_beta(armn=4,a1=56,b1=98,a2=25,b2=70,a3=87,b3=107,
a4=106, b4=202, side='lower')
pmax_beta(armn=3,a1=60,b1=46,a2=55,b2=46,a3=35,b3=36,side='upper')