plot {MAMS}

Different generic functions for class MAMS.

Description

Generic functions for summarizing an object of class MAMS.

Usage

## S3 method for class 'MAMS'
print(x, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS'
summary(object, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS'
plot(x, col=NULL, pch=NULL, lty=NULL, main=NULL, xlab="Analysis", 
     ylab="Test statistic", ylim=NULL, type=NULL, las=1, ...)

## S3 method for class 'MAMS.sim'
print(x, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS.sim'
summary(object, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS.stepdown'
print(x, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS.stepdown'
summary(object, digits=max(3, getOption("digits") - 4), ...)

## S3 method for class 'MAMS.stepdown'
plot(x, col=NULL, pch=NULL, lty=NULL, main=NULL, xlab="Analysis", 
     ylab="Test statistic", ylim=NULL, type=NULL, bty="n", las=1, ...)

Arguments

x

An output object of class MAMS.

digits

Number of significant digits to be printed.

object

An output object of class MAMS.

col

A specification for the default plotting color (default=NULL). See par for more details.

pch

Either an integer specifying a symbol or a single character to be used as the default in plotting points (default=NULL). See par for more details.

lty

A specification for the default line type to be used between analyses (default=NULL). Setting to zero supresses ploting of the lines. See par for more details.

main

An overall title for the plot (default=NULL).

xlab

A title for the x axis (default="Analysis").

ylab

A title for the y axis (default="Test statistic").

ylim

Numeric vector of length 2, giving the y coordinates range (default=NULL).

type

Type of plot to be used (default=NULL). See plot for more details.

bty

Should a box be drawn around the legend? The default "n" does not draw a box, the alternative option "o" does.

las

A specification of the axis labeling style. The default 1 ensures the labels are always horizontal. See ?par for details.

...

Further (graphical) arguments to be passed to methods.

Details

print.MAMS produces a summary of an object from class MAMS including boundaries and requires sample size if initially requested.

summary.MAMS produces same output as print.MAMS.

plot.MAMS produces as plot of the boundaries.

print.MAMS.sim produces a summary of an object from class MAMS.sim including type-I-error and expected sample size.

summary.MAMS.sim produces same output as print.MAMS.sim.

print.MAMS.stepdown produces a summary of an object from class MAMS including boundaries and requires sample size if initially requested.

summary.MAMS.stepdown produces same output as print.stepdown.mams.

plot.MAMS.stepdown produces a plot of the boundaries. When used with stepdown.update, pluses indicate observed values of test statistics.

Value

Screen or graphics output.

Author(s)

Thomas Jaki, Dominic Magirr, Philip Pallmann

References

Magirr D, Jaki T, Whitehead J (2012) A generalized Dunnett test for multi-arm multi-stage clinical studies with treatment selection. Biometrika, 99(2), 494-501.

Stallard N, Todd S (2003) Sequential designs for phase III clinical trials incorporating treatment selection. Statistics in Medicine, 22(5), 689-703.

Magirr D, Stallard N, Jaki T (2014) Flexible sequential designs for multi-arm clinical trials. Statistics in Medicine, 33(19), 3269-3279.

See Also

mams, stepdown.mams, MAMS.

Examples

# 2-stage design with triangular boundaries
res <- mams(K=4, J=2, alpha=0.05, power=0.9, r=1:2, r0=1:2, p=0.65, p0=0.55, 
            ushape="triangular", lshape="triangular", nstart=30)

print(res)
summary(res)
plot(res)

res <- mams.sim(nsim=10000, nMat=matrix(c(44, 88), nrow=2, ncol=5), u=c(3.068, 2.169),
                l=c(0.000, 2.169), pv=c(0.65, 0.55, 0.55, 0.55), ptest=c(1:2, 4))

print(res)

# 2-stage 3-treatments versus control design, all promising treatments are selected:
res <- stepdown.mams(nMat=matrix(c(10, 20), nrow=2, ncol=4), 
                     alpha.star=c(0.01, 0.05), lb=0, 
                     selection="all.promising")

print(res)
summary(res)
plot(res)