Asked 10th Apr, 2022

What is a good method to select variables for Cox Regression?

Dear biostats community,
I am trying to build a Cox (Proportional Hazards) Regression and have a dataset with several variables. I am trying to decide which variables are the most useful to use as covariates in my model. Which method do you use and recommend for doing this? I thought at first to do a univariate analysis and see which variables don't have a significant survival difference to exclude them but as I understand such procedures have the issue that they don't take into account the interaction between the different variables.
Thank you very much!!

All Answers (3)

10th Apr, 2022
Bhogaraju Anand
Malla Reddi Institute of Medical Sciences
Intuitively selecting based upon already associated covariates from literature. another way is step-wise selection.
This is a reference link for different methods which can be used.:
Garcia, R. I., Ibrahim, J. G., & Zhu, H. (2010). Variable selection in the cox regression model with covariates missing at random. Biometrics, 66(1), 97–104.
For a theoretical discussion:
Handbook of Survival Analysis by John P. Klein, CRC Press Taylor & Francis Group
1 Recommendation
10th Apr, 2022
David Eugene Booth
Kent State University
Stepwise would be a terrible choice. I recommend lasso or the adaptive lasso version. See the attached papers. Best wishes, David Booth

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