# 2.5: Conditional Power at Interim Boundaries

### Description

`gsBoundCP()`

computes the total probability of crossing future upper bounds given an interim test statistic at an interim bound.
For each interim boundary, assumes an interim test statistic at the boundary and
computes the probability of crossing any of the later upper boundaries.

### Usage

1 | ```
gsBoundCP(x, theta="thetahat", r=18)
``` |

### Arguments

`x` |
An object of type |

`theta` |
if |

`r` |
Integer value controlling grid for numerical integration as in Jennison and Turnbull (2000);
default is 18, range is 1 to 80.
Larger values provide larger number of grid points and greater accuracy.
Normally |

### Details

See Conditional power section of manual for further clarification. See also Muller and Schaffer (2001) for background theory.

### Value

A list containing two vectors, `CPlo`

and `CPhi`

.

`CPlo` |
A vector of length |

`CPhi` |
A vector of length |

### Note

The manual is not linked to this help file, but is available in library/gsdesign/doc/gsDesignManual.pdf in the directory where R is installed.

### Author(s)

Keaven Anderson keaven\_anderson@merck.

### References

Jennison C and Turnbull BW (2000), *Group Sequential Methods with Applications to Clinical Trials*.
Boca Raton: Chapman and Hall.

Muller, Hans-Helge and Schaffer, Helmut (2001), Adaptive group sequential designs for clinical trials:
combining the advantages of adaptive and classical group sequential approaches. *Biometrics*;57:886-891.

### See Also

`gsDesign`

, `gsProbability`

, `gsCP`

### Examples

1 2 3 4 5 6 7 8 9 |