| CatPredi-package {CatPredi} | R Documentation |
Categorisation of Continuous Predictor Variables in Regression Models.
Description
Allows the user to categorise a continuous predictor variable in a logistic or a Cox proportional hazards regression setting, by maximising the discriminative ability of the model. The categorisation can be done either in a univariate or a multivariate setting.
Author(s)
Irantzu Barrio, Maria Xose Rodriguez-Alvarez and Inmaculada Arostegui
Maintainer: Irantzu Barrio <irantzu.barrio@ehu.eus>
References
I Barrio, I Arostegui, M.X Rodriguez-Alvarez and J.M Quintana (2015). A new approach to categorising continuous variables in prediction models: proposal and validation. Statistical Methods in Medical Research, in press.
I Barrio, M.X Rodriguez-Alvarez, L Meira-Machado, C Esteban and I Arostegui (2017). Comparison of two discrimination indexes in the categorisation of continuous predictors in time-to-event studies. SORT, 41:73-92