logit {cutoff}

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)