ibetabinomial.post {BayesianPlatformDesignTimeTrend} | R Documentation |

## ibetabinomial.post

### Description

This function calculates the posterior probability of each active treatment arm better than control using betabinomial model

### Usage

```
ibetabinomial.post(n, y, pi.star = 0.5, pess = 2)
```

### Arguments

`n` |
A vector of treated patients for each arm (The first element is for control) |

`y` |
A vector of treated patient outcomes for each arm (The first element is for control) |

`pi.star` |
The prior response probability. The default is 0.5 |

`pess` |
The effective sample size of beta prior. The default is 2 |

### Value

A vector posterior probability of each active treatment arm better than control

### Author(s)

Ziyan Wang

### Examples

```
n <- c(20,20,20,20)
y <- c(12,12,12,6)
ibetabinomial.post(n, y, pi.star = 0.5, pess = 2)
#[1] 0.5000000 0.5000000 0.0308018
```

[Package

*BayesianPlatformDesignTimeTrend*version 1.2.3 Index]