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CatPredi (version 1.4)

CatPredi-package: 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.

Arguments

Author

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

Maintainer: Irantzu Barrio <irantzu.barrio@ehu.eus>

References

I Barrio, J Roca-Pardinas and I Arostegui (2021). Selecting the number of categories of the lymph node ratio in cancer research: A bootstrap-based hypothesis test. Statistical Methods in Medical Research, 30(3), 926-940.

I Barrio, I Arostegui, M.X Rodriguez-Alvarez and J.M Quintana (2017). A new approach to categorising continuous variables in prediction models: proposal and validation. Statistical Methods in Medical Research, 26(6), 2586-2602.

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