I've submitted a manuscript to a journal and the associate editor wrote that his readers will want to know more about how the predictor of main interest (occupation) is related to death, and this will require, according to the editor, more complex statistical modeling.
What is it all about? I examined how occupation relates to death in individuals with coronary heart disease. I've, as conventional, performed survival analysis with the following characteristics:
- Cox regression.
- I have multiple observations for each individual and virtually all covariates are updated at each observation! The extended Cox model, in counting process syntax, performed with rms package by Harrell, has been used.
- Continuous predictors are modeled with restricted cubic splines, using 4 knots.
- Large cohort >50,000 observations, >10,000 individuals.
- I have adjusted for all known, and additionally some presumed, risk factors for the outcome of interest. After doing this, occupation remains a strong predictor of death.
- So I arrived in the conclusion that occupation is an independent predictor of death, regardless of known risk factors and presumed risk factors. (I've adjusted for up to 15 covariates).
What more can I do? What "complex statistical modeling" is the editor seeking?
I'd be grateful for some help.