logrank: Significant Cutoff Value for Logrank Analysis

In cutoff: Seek the Significant Cutoff Value

Description

Significant Cutoff Value for Logrank Analysis

Usage

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

Arguments

data	data
time	name for time variable
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, beta of regression and p value.

Examples

logrank(data=mtcars,
        time = 'disp',y='am', x='wt',
        cut.numb=2,
        n.per=0.25,
        y.per=0.10)

logrank(data=mtcars,
        time = 'disp',y='am', x='wt',
        cut.numb=2,
        n.per=0.25,
        y.per=0.10,
        p.cut=0.05,
        strict=TRUE,
        include='low',
        round=2)

cutoff documentation built on Jan. 11, 2020, 9:39 a.m.