gsbDesign (version 1.0-3)

plot.gsbMainOut: Plot methods

Description

Methods for plotting the results of gsb().

Usage

# S3 method for gsbMainOut
plot(x,
     what=c("all", "cumulative all",
            "both", "cumulative both",
            "sample size", "success", "futility",
            "success or futility", "indeterminate", "cumulative success",
            "cumulative futility", "cumulative success or futility",
            "cumulative indeterminate", "boundary",
            "std.boundary","delta.grid","patients"),
     range.delta = "default",
     stages = "default",
     delta.grid = TRUE,
     color = TRUE,
     smooth = 100,
     contour = TRUE, 
     export = FALSE,
     path = tempdir(),
     sliced = FALSE,
     range.control="default", ...)
# S3 method for gsbSimulation
plot(x,...)
# S3 method for gsbDesign
plot(x,...)

Value

Returns an object of class "trellis"

Arguments

x

object of appropriate class.

what

a character string to choose a plot. It should correspond to one level of OC$type where OC is an object of the output of gsb(). Additional possibilities are what = "all" to plot the success-, futility- and success or futility-probabilities, what = "cumulative all" to plot the cumulative success-, cumulative futility- and cumulative success or futility-probabilities, what = "boundary" or what = "std.boundary" to plot the bounds, what = "patients" for a histogram of the patients per stage and what = "delta.grid" to plot the grid of delta's.

range.delta

a vector of length 2. For choosing the plot limits manually set range.delta = c(min, max) for a Bayesian update on "treatment effect" or
range.delta = c(control.min, control.max, treatment.min, treatment.max) for a Bayesian update "per arm". If range.delta = "default" the range of the plot is chosen so that all delta's are covered.

stages

a vector of length 2 containing the number of the lowest and highest stage, which should be plotted. If stages = "default" all stages are plotted (expect for what = "sample size" where only the last stage is plotted.)

delta.grid

logical. If TRUE the delta grid is plotted too.

color

logical. If TRUE the plot is colored.

smooth

a vector of length 1. A higher number makes the plot 'smoother' if type.update = "per arm".

contour

logical. If TRUE contour lines are added to the plot.

export

logical. If TRUE the plot is save as .png-file.

path

character. to specify the location to which to table should be exported. the default 'tempdir()' exports the table to a temporary directory.

sliced

logical. If TRUE the contour plot for type.update = "per arm" is shown in several 2D plots. In order to use this option the argument grid.type of gsbSimulation() has to be sliced.

range.control

a vector of length 2 or \"default\". If special = TRUE the range of the control values can be set manually as vector c(min, max).

...

further arguments passed to or from other methods.

Author

Florian Gerber <[e-mail]>, Thomas Gsponer

References

uses the R-package 'lattice'.

See Also

gsb, xyplot

Examples

## please see examples of function 'gsb'. 
## --------------------------------------


## --------------------------------------
## alternative plots can be created for example
## with package 'ggplot2'.
# \donttest{
des <- gsbDesign(nr.stages=2,
                     patients=10,
                     sigma=10,
                     criteria.success=c(0,0.8, 7, 0.5),
                     criteria.futility=c(2,0.8),
                     prior.difference="non-informative")

sim <- gsbSimulation(truth=c(-10,20,60),
                             type.update="treatment effect")


x <- gsb(des,sim)

## get data.frame with operating characteristics
datgraph <- x$OC


## prepare for plot
sub <- c("success", "futility", "success or futility")
datgraph2 <- subset(datgraph,datgraph$type %in% sub)
datgraph2$type <- as.factor(paste(datgraph2$type))
datgraph2$value[datgraph2$type=="cumulative success or futility"] <-
1-datgraph2$value[datgraph2$type=="cumulative success or futility"]
levels(datgraph2$type) <- c("1)cumulative futility" ,"3)cumulative success","2)indeterminate")
datgraph2$type=as.factor(paste(datgraph2$type))
levels(datgraph2$type) <- c("cumulative futility" ,"indeterminate","cumulative success")
datgraph2 <- datgraph2[order(datgraph2$delta),]


## plots
library(ggplot2)
p1 <- qplot(delta,value,geom="blank",color=type,facets=.~stage,data=datgraph2,
xlab=expression(delta))

p1+geom_line(size=1.5)+scale_color_manual(values = c("cumulative futility" = "dark red",
"indeterminate" = "orange", "cumulative success" = "dark green"))

p2=p1+geom_area(aes(x = delta,y=value,fill=type))

p2+scale_fill_manual(values = c("cumulative futility" = "dark red",
"indeterminate" = "orange", "cumulative success" = "dark green"))

# }