binom_one_assurance {EurosarcBayes}

Single arm, assurance calculator for single or multi-stage binomial trials.

Description

Computes the assurance of a given trial design given a prior assurance distribution.

Usage

binom_one_assurance(failure, success, n, ass.dist,
 type="continuous", lower=0, upper=1, ...)

plot_binomassurance(failure, success, n, ass.dist,type="continuous",
	ndivisions=1000, xlim=c(0,1), xaxs="i", yaxs="i", ylim=NULL,
	main="Assurance distribution", col="red", col.fill="green", lwd=2,
	xlab="Probability of successful treatment",
	ylab="Prior assurance probability" ,...)

Arguments

failure

A vector of the number of failures required to stop for futility, if not able to stop NA or a character string should be provided

success

A vector of the number of successes required to stop for efficacy, if not able to stop NA or a character string should be provided

n

A vector of the total number of patients to recruit up to each stage of the trial

ass.dist

Distribution of prior probability for assurance. May be different to prior information.

type

Tells the program you are passing it a continuous distribution ("continuous") or a discrete distribution ("discrete") for the assurance distribution

ndivisions

The number of points calculated for the plot

lower, upper

Range of the distribution to use

col.fill

Colour of the true positive results in the graph

xlim, xaxs, yaxs, ylim, main, col, lwd, xlab, ylab

Different defaults for plotting parameters

...

Additional plotting parameters to pass to plot function

See Also

binom_one_power, binom_one_alpha

Examples

# Simon's two stage design
failure=c(0,3)
success=c(NA,4)
n=c(7,18)
p0=0.1
p1=0.3

# continuous assurance distribution
ass.dist = function(p) dbeta(p,4,18)

# assurance
binom_one_assurance(failure,success,n,ass.dist)

# plot
plot_binomassurance(failure,success,n,ass.dist,ndivisions=1000)

# discrete assurance distribution
ass.dist = matrix(c(0.2,0.3,0.4,0.3,0.4,0.3),ncol=2)

# assurance
binom_one_assurance(failure,success,n,ass.dist,type="discrete")

# plot
plot_binomassurance(failure,success,n,ass.dist,type="discrete",
                    ndivisions=1000)