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 (Beta(\alpha,\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 Pr(p_k=max\{p_1,...,p_K\})
for
side
equals to 'upper' and the results of formula Pr(p_k=min\{p_1,...,p_K\})
for
side
equals to 'lower'. This function returns the probability that the posterior probability of arm
k
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')