bayes.design: Bayesian design method for sequentially monitoring patients...

Description Usage Arguments Value References Examples

Description

Make animation plots to present sequential monitor stopping rule using Beta-Binomial Bayesian model

Usage

1
2
bayes.design(a,b,r=0, stop.rule="futility", add.size=5, alpha=0.05,
p0 ,delta=0.2,tau1=0.9,tau2=0.9,tau3=0.9,tau4=0.9, time.interval =1)

Arguments

a

the hyperparameter (shape1) of the Beta prior for the experimental drug.

b

the hyperparameter (shape2) of the Beta prior for the experimental drug.

r

the maximum number of patients treated by the experimental drug.

stop.rule

the hyperparameter (shape1) of the Beta prior for the experimental drug.

add.size

a single integer value, random number generator (RNG) state for random number generation.

alpha

the siginificant level to determine the credible interval, set 0.05 by default.

p0

the prespecified reseponse rate.

delta

the minimally acceptable increment of the response rate.

tau1

threshold for stopping rule 1.

tau2

threshold for stopping rule 2.

tau3

threshold for stopping rule 3.

tau4

threshold for stopping rule 4.

time.interval

a positive number to set the time interval of the animation (unit in seconds); default to be 1.

Value

animation plot of determination of stopping boundaries.

References

Yin, G. (2012). Clinical Trial Design: Bayesian and Frequentist Adaptive Methods. New York: Wiley.

Examples

1
2
3
4
5
6
7
8
9
# Using Multiple Myeloma (MM) data example
MM.r = rep(0,6); MM.mean = 0.1; MM.var = 0.0225
a <- MM.mean^2*(1-MM.mean)/MM.var - MM.mean; b <- MM.mean*(1-MM.mean)^2/MM.var - (1-MM.mean)
bayes.design(a=a,b=b,r=MM.r,stop.rule="futility",p0=0.1)

# Using Acute Promyelocytic Leukaemia (APL) data example
APL.r <- c(0,1,0,0,1,1); APL.mean = 0.3; APL.var = 0.0191
a <- APL.mean^2*(1-APL.mean)/APL.var - APL.mean; b <- APL.mean*(1-APL.mean)^2/APL.var - (1-APL.mean)
bayes.design(a=a,b=b,r=APL.r,stop.rule="efficacy",p0=0.1)


Search within the ph2bye package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.