Description Usage Arguments Details Value Author(s) References See Also Examples

This function computes the boundary of the decision region in a manner that can be employed in the field, as a table, for example. See section 4.2 of the reference below.

1 | ```
computeBoundary(b1, b0, p, glrTables = NULL, tol=1e-7)
``` |

`b1` |
The acceptance boundary value (corresponds to the boundary |

`b0` |
The rejection boundary value (corresponds to the boundary |

`p` |
The vector of probabilities, |

`glrTables` |
A previously computed set of likelihood functions, to speed up
computation for the |

`tol` |
A numerical tolerance, defaults to 1e-7 |

This essentially computes the probabilities of hitting the boundaries using a recursion.

`upper` |
The upper boundary that indicates rejection of the null hypothesis |

`lower` |
The upper boundary that indicates acceptance of the null hypothesis |

`estimate ` |
The estimated |

Balasubramanian Narasimhan

Mei-Chiung Shih, Tze Leung Lai, Joseph F. Heyse, and Jie Chen. Sequential Generalized Likelihood Ratio Tests for Vaccine Safety Evaluation (Statistics in Medicine, Volume 29, issue 26, p.2698-2708, 2010.)

Please also consult the website http://med.stanford.edu/biostatistics/ClinicalTrialMethodology/ for further developments.

See Also `glrSearch`

1 | ```
computeBoundary(b1=2.8, b0=3.3, p=c(.5, .75))
``` |

```
Loading required package: ggplot2
Loading required package: shiny
$upper
[1] NA NA NA NA 5 6 7 8 9 9 10 11 11 12 13 13 14 15 15 16 17 17 18 19 19
[26] 20 21 21 22 22 23 24 24 25 25 26 27 27 28 29 29 30 30 31 32 32 33 33 34 34
[51] 35 36 36 37 37 38 39 39 40 40 41 42 42 43 43 44 44 45 46 46 47 47 48 48 49
[76] 50 50 51 51 52 52 53 54 54 55 55 56 56 57 58 58
$lower
[1] NA NA 0 0 1 1 2 2 3 3 4 5 5 6 6 7 8 8 9 10 10 11 11 12 13
[26] 13 14 15 15 16 17 17 18 19 19 20 21 21 22 23 23 24 25 25 26 27 27 28 29 29
[51] 30 31 31 32 33 33 34 35 35 36 37 38 38 39 40 40 41 42 42 43 44 44 45 46 46
[76] 47 48 49 49 50 51 51 52 53 53 54 55 55 56 57 58
$estimate
alpha beta
0.06045524 0.06606180
```

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