rpact: Confirmatory Adaptive Clinical Trial Design and Analysis
plot.StageResults {rpact}  R Documentation 
Stage Results Plotting
Description
Plots the conditional power together with the likelihood function.
Usage
## S3 method for class 'StageResults'
plot(
x,
y,
...,
type = 1L,
nPlanned,
allocationRatioPlanned = 1,
main = NA_character_,
xlab = NA_character_,
ylab = NA_character_,
legendTitle = NA_character_,
palette = "Set1",
legendPosition = NA_integer_,
showSource = FALSE
)
Arguments
x 
The stage results at given stage, obtained from getStageResults or getAnalysisResults .

y 
Not available for this kind of plot (is only defined to be compatible to the generic plot function).

... 
Optional plot arguments. Furthermore the following arguments can be defined:

thetaRange : A range of assumed effect sizes if testing means or a survival design was specified.
Additionally, if testing means was selected, an assumed standard deviation can be specified (default is 1).

piTreatmentRange : A range of assumed rates pi1 to calculate the conditional power.
Additionally, if a twosample comparison was selected, pi2 can be specified (default is the value from
getAnalysisResults ).

directionUpper : Specifies the direction of the alternative,
only applicable for onesided testing; default is TRUE
which means that larger values of the test statistics yield smaller pvalues.

thetaH0 : The null hypothesis value, default is 0 for the normal and the binary case,
it is 1 for the survival case.
For testing a rate in one sample, a value thetaH0 in (0,1) has to be specified for
defining the null hypothesis H0: pi = thetaH0.

type 
The plot type (default = 1). Note that at the moment only one type
(the conditional power plot) is available.

nPlanned 
The additional (i.e., "new" and not cumulative) sample size planned for each of the subsequent stages.
The argument must be a vector with length equal to the number of remaining stages and contain
the combined sample size from both treatment groups if two groups are considered. For survival outcomes,
it should contain the planned number of additional events.
For multiarm designs, it is the percomparison (combined) sample size.

allocationRatioPlanned 
The planned allocation ratio n1 / n2 for a two treatment groups
design, default is 1 . For multiarm designs, it is the allocation ratio relating the active arm(s) to the control.

main 
The main title.

xlab 
The xaxis label.

ylab 
The yaxis label.

legendTitle 
The legend title.

palette 
The palette, default is "Set1" .

legendPosition 
The position of the legend.
By default (NA_integer_ ) the algorithm tries to find a suitable position.
Choose one of the following values to specify the position manually:

1 : no legend will be shown

NA : the algorithm tries to find a suitable position

0 : legend position outside plot

1 : legend position left top

2 : legend position left center

3 : legend position left bottom

4 : legend position right top

5 : legend position right center

6 : legend position right bottom

showSource 
If TRUE , the parameter names of the object will
be printed which were used to create the plot; that may be, e.g.,
useful to check the values or to create own plots with the base R plot function.
Alternatively showSource can be defined as one of the following character values:

"commands" : returns a character vector with plot commands

"axes" : returns a list with the axes definitions

"test" : all plot commands will be validated with eval(parse()) and
returned as character vector (function does not stop if an error occurs)

"validate" : all plot commands will be validated with eval(parse()) and
returned as character vector (function stops if an error occurs)
Note: no plot object will be returned if showSource is a character.

Details
Generic function to plot all kinds of stage results.
The conditional power is calculated only if effect size and sample size is specified.
Value
Returns a ggplot2
object.
Examples
design < getDesignGroupSequential(kMax = 4, alpha = 0.025,
informationRates = c(0.2, 0.5, 0.8, 1),
typeOfDesign = "WT", deltaWT = 0.25)
dataExample < getDataset(
n = c(20, 30, 30),
means = c(50, 51, 55),
stDevs = c(130, 140, 120)
)
stageResults < getStageResults(design, dataExample, thetaH0 = 20)
if (require(ggplot2)) plot(stageResults, nPlanned = c(30), thetaRange = c(0, 100))