# The predictive probability criterion function

### Description

Lee and Liu's criterion function for determining the trial decision cutoffs based on the predictive probability.

### Usage

1 | ```
predprob(y, n, nmax, alpha_e, beta_e, p_s, theta_t)
``` |

### Arguments

`y` |
the number of responses among |

`n` |
the number of patients treated by the experimental drug at a certain stage of the trial. |

`nmax` |
the maximum number of patients treated by the experimental drug. |

`alpha_e` |
the hyperparameter (shape1) of the Beta prior for the experimental drug. |

`beta_e` |
the hyperparameter (shape2) of the Beta prior for the experimental drug. |

`p_s` |
the the response rate for the standard drug. |

`theta_t` |
the prespecified target probability; tipically, |

### Value

`prob` |
the predictive probability: |

### References

Lee, J. J., Liu, D. D. (2008).
A predictive probability design for phase II cancer clinical trials.
*Clinical Trials* **5**: 93-106.

Yin, G. (2012).
*Clinical Trial Design: Bayesian and Frequentist Adaptive Methods.*
New York: Wiley.

### Examples

1 2 | ```
# p. 97, PP = 0.5656
predprob(16, 23, 40, 0.6, 0.4, 0.6, 0.9)
``` |

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.