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,
plotSettings = NULL
)


### 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 two-sample comparison was selected, pi2 can be specified (default is the value from getAnalysisResults()). directionUpper: Specifies the direction of the alternative, only applicable for one-sided testing; default is TRUE which means that larger values of the test statistics yield smaller p-values. 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 multi-arm designs, it is the per-comparison (combined) sample size. For enrichment designs, it is the (combined) sample size for the considered sub-population. allocationRatioPlanned The planned allocation ratio n1 / n2 for a two treatment groups design, default is 1. For multi-arm designs, it is the allocation ratio relating the active arm(s) to the control. main The main title. xlab The x-axis label. ylab The y-axis 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 Logical. 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. plotSettings An object of class PlotSettings created by getPlotSetting()s.

### 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))


[Package rpact version 3.3.2 Index]