# Summary

This R Markdown document
provides different examples for creating one- and multi-arm analysis
result plots with rpact and ggplot2.

# Preparation

**First, load the rpact package**

```
library(rpact)
packageVersion("rpact") # version should be version 3.0 or later
```

`## [1] '3.3.2'`

# Create a design

```
designIN <- getDesignInverseNormal(
kMax = 4, alpha = 0.02,
futilityBounds = c(-0.5, 0, 0.5), bindingFutility = FALSE,
typeOfDesign = "asKD", gammaA = 1.2,
informationRates = c(0.15, 0.4, 0.7, 1)
)
designF <- getDesignFisher(
kMax = 4, alpha = 0.02,
informationRates = c(0.15, 0.4, 0.7, 1)
)
```

# Analysis results
base

## Analysis results base
- means

```
simpleDataExampleMeans1 <- getDataset(
n = c(120, 130, 130),
means = c(0.45, 0.51, 0.45) * 100,
stDevs = c(1.3, 1.4, 1.2) * 100
)
x <- getAnalysisResults(
design = designIN, dataInput = simpleDataExampleMeans1,
nPlanned = 130, thetaH0 = 30, thetaH1 = 60, assumedStDev = 100
)
```

`## Calculation of final confidence interval performed for kMax = 4 (for kMax > 2, it is theoretically shown that it is valid only if no sample size change was performed)`

`plot(x, thetaRange = c(10, 80))`