logit {cutoff} R Documentation

## Significant Cutoff Value for Logistic Regression

### Description

Significant Cutoff Value for Logistic Regression

### Usage

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


### Arguments

 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

### Value

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

### Examples

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]