logit {cutoff} | R Documentation |

Significant Cutoff Value for Logistic Regression

```
logit(data, y, x, cut.numb, n.per, y.per, p.cut = 0.05, strict = TRUE,
include = "low", round = 2, adjust = 1)
```

`data` |
data |

`y` |
name for y, must be coded as 1 and 0. The outcome must be 1 |

`x` |
name for x |

`cut.numb` |
number of cutoff points |

`n.per` |
the least percentage of the smaller group comprised in all patients |

`y.per` |
the least percentage of the smaller outcome patients comprised in each group |

`p.cut` |
cutoff of p value, default is 0.05 |

`strict` |
logical. TRUE means significant differences for each group combination were considered. FALSE means considering for any combination |

`include` |
direction of cutoff point. Any left letter of lower or upper |

`round` |
digital. Default is 2 |

`adjust` |
numeric value, adjust methord for p value. 1, defaulted, represents Bonferroni. 2 represent formula given by Douglas G in 1994 |

a dataframe contains cutoff points value, subject numbers in each group, dumb variable, or of regression and p value.

```
logit(data=mtcars,
y='am',
x='disp',
cut.numb=1,
n.per=0.25,
y.per=0.25)
logit(data=mtcars,
y='am',
x='disp',
cut.numb=1,
n.per=0.25,
y.per=0.20,
p.cut=0.05,
strict=TRUE,
include='low',
round=2)
```

[Package *cutoff* version 1.3 Index]