# p-value of hypothesis test that the cutover of a blended link is equal to a specific value

### Description

This function calculates an asymptotic chi-square likelihood ratio hypothesis test of a specified null hypothesis for the cutover.

### Usage

1 |

### Arguments

`data` |
a data frame containing the variables in the model. |

`formula` |
an object of class formula, a symbolic description of the model to be fitted, see help(glm) |

`link1` |
Character string indicating the link function to be used up to the cutover |

`link2` |
Character string indicating the link function to be used above the cutover |

`cutover0` |
The hypothesized value of the cutover at which the link function switches smoothly from link1 to link2. Must be strictly greater than 0 and strictly less than 1. |

`eps` |
A tuning parameter. The MLE of the cutover is restricted to the range eps to (1-eps). Usually eps=0 is appropriate, but occasionally a small positive value may be needed to avoid numerical problems in the maximisation of the likelihood. |

### Details

Binary regression is assumed. Not suitable when the null value is on the boundary (i.e. when cutover0 is 0 or 1).

### Value

The p-value of a test of the null hypothesis that cutover=cutover0.

### Examples

1 2 | ```
pvalue.cutover(y~x1+x2 , data=loglogit.example,link1="log",link2="logit",
cutover0=0.8)
``` |