rpact (version 1.0.0)

AnalysisResults_plot: Analysis Results Plotting - Conditional Power Plot

Description

Plots the conditional power together with the likelihood function.

Usage

# S3 method for AnalysisResults
plot(x, y, ..., nPlanned = NA_real_,
  stage = x$getNumberOfStages(), allocationRatioPlanned = NA_real_,
  main = NA_character_, xlab = NA_character_, ylab = NA_character_,
  legendTitle = "", palette = "Set1", legendPosition = NA_integer_,
  type = 1L)

Arguments

x

The analysis results at given stage, obtained from getAnalysisResults.

y

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

...

Optional ggplot2 arguments.

nPlanned

The sample size planned for the subsequent stages. It should be a vector with length equal to the remaining stages and is the overall sample size in the two treatment groups if two groups are considered.

stage

The stage number (optional). Default: total number of existing stages in the data input used to create the analysis results.

allocationRatioPlanned

The allocation ratio n1/n2 for two treatment groups planned for the subsequent stages, the default value is 1.

main

The main title, default is "Dataset".

xlab

The x-axis label, default is "Stage".

ylab

The y-axis label.

legendTitle

The legend title, default is "".

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:

• 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

type

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

Details

The conditional power is calculated only if effect size and sample size is specified.

Examples

# NOT RUN {
design <- getDesignGroupSequential(kMax = 2)

dataExample <- getDataset(
    n = c(20, 30),
	   means = c(50, 51),
	   stDevs = c(130, 140)
)

result <- getAnalysisResults(design = design, 
	   dataInput = dataExample, thetaH0 = 20, 
	   nPlanned = c(30), thetaH1 = 1.5, stage = 1) 

if (require(ggplot2)) plot(result, thetaRange = c(0, 100))

# }