Cox regression and covariate selection

When selecting covariates to adjust for baseline confounding, such as sex and age, in a Cox regression, do we evaluate change in estimate for each covariate to decide whether to include in the model as we would in logistic regression?

Thanks much!

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As explained in detail in my book Regression Modeling Strategies, it is not good statistical practice to “play” with the model. There are many reasons for this, including

  • the judgement of how big a “change” is arbitrary
  • this procedure will result in biased (low) estimates of standard errors of the parameter estimates

My recommendation is to pre-specify the model and to include all the pre-specified covariates no matter how insignificant they are.

I assume you have an observational study.


yes, it’s an observational study. i agree i would normally select covariates based on literature review and biological relevance and then draw a DAG. just wanted to make sure i am not missing anything.

many thanks!


I guess another reason not to use change-in-estimates is that it cannot distinguish between confounders and mediators, right?

You don’t need to think that deeply. Just use that fact that the change-in-estimates method is not based on any statistical principles and it ruins estimates of uncertainty. It also suggests that parsimony is a good thing. I suggest never using it.

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