BAC_binom {BACCT}R Documentation

Bayesian Augmented Control for Binary Responses


Calling JAGS to implement BAC for binary responses


BAC_binom(yh, nh, n1, n2, y1.range = 0:n1, y2.range = 0:n2, n.chain = 5,
  tau.alpha = 0.001, tau.beta = 0.001, prior.type = "nonmixture",
  criterion.type = c("diff", "prob"), prob.threshold, sim.mode = c("full",


yh, nh

Vector of the numbers of events (subjects) in the historical trial(s). Must be of equal length.

n1, n2

Number of subjects in the control or treatment arm of the current trial.

y1.range, y2.range

Number of events in control or treatment arm of the current trial. See "Details".


Controls the number of posterior samples. Each chain contains 20,000 samples.

tau.alpha, tau.beta

Hyperparameters of the inverse gamma distribution controling the extent of borrowing.


Type of prior on control groups. Currenly, only the inverse-gamma prior is implemented.


Type of posterior quantities to be monitored. See "Details."


For criterion.type="prob" only. See "Details".


Simulation duration reduces greatly in "express" mode, if treatment and control arms are independent. See "Details".


There are two types of posterior quantities for criterion.type argument. With "diff" option, the quantity computed is p_{T} - p_{C}; with "prob," such quantity is pr(p_{T} - p_{C}>\Delta), where \Delta is specified by prob.threshold argument.

By default, y1.range and y2.range cover all possible outcomes and should be left unspecified in most cases. However, when n1 and/or n2 is fairly large, it is acceptable to use a reduced range that covers the outcomes that are most likely (e.g., within 95% CI) to be observed. This may help shorten the time to run MCMC.

Another way that can greatly shorten the MCMC running time is to specify "express" mode in sim.mode argument. Express mode reduces the number of simulations from length(y1.range)*length(y2.range) to length(y1.range)+length(y2.range). Express mode is proper when the treatment arm rate is independent of control arm rate.


An object of class "BAC".


Hongtao Zhang


## Not run: 
#borrow from 3 historical trials#
yh = c(11,300,52);nh = c(45,877,128)
#specify current trial sample sizes#
n1 = 20;n2 = 30

#Difference criterion type in full simulation mode#
obj1 = BAC_binom(yh=yh,nh=nh,n1=n1,n2=n2,n.chain=5,

#Probability criterion type in express simulation mode#
obj2 = BAC_binom(yh=yh,nh=nh,n1=n1,n2=n2,n.chain=5,

#S3 method for class "BAC"

## End(Not run)

[Package BACCT version 1.0 Index]