controlcatpredi: Control function

In CatPredi: Optimal Categorisation of Continuous Variables in Prediction Models

Control function

Description

Function used to set several parameters to control the selection of the optimal cut points in a logistic regression model

Usage

controlcatpredi(
  min.p.cat = 1,
  grid = 100,
  B = 50,
  eps = 0.001,
  b.method = c("ncoutcome", "coutcome"),
  print.gen = 0
)

Arguments

min.p.cat	Set the minimun number of individuals in each category
grid	Grid size for the AddFor and BackAddFor algorithms
B	Number of bootstrap replicates for the AUC bias correction procedure
eps	An argument for the BackAddFor algorithm, indicating whether the improvement between iterations is considered significant
b.method	Allows to specify whether the bootstrap resampling should be done considering or not the outcome variable. The option "ncoutcome" indicates that the data is resampled without taking into account the response variable, while "coutcome" indicates that the data is resampled in regard to the response variable
print.gen	Corresponds to the argument print.level of the genoud function of the package rgenoud.

Value

A list with components for each of the possible arguments.

Author(s)

Irantzu Barrio, Maria Xose Rodriguez-Alvarez, Inmaculada Arostegui, Javier Roca-Pardinas and Xabier Amutxastegi.

References

Mebane Jr, W. R., & Sekhon, J. S. (2011). Genetic optimization using derivatives: the rgenoud package for R. Journal of Statistical Software 4211, 1-26.

See Also

catpredi

CatPredi documentation built on May 8, 2026, 9:07 a.m.