I am performing a cox proportional hazard regression on survival, in a sample in which almost everyone dies in the follow up period. I have little knowledge on statistics in general but i am reading as much as I can and try to move carefully. I want to be sure to thoroughly check the PH assumption. I can get some help from a statistician, but it takes 2 weeks til i can get an appointment (I will!)
I found 2 methods for checking the PH assumption that i can easily perform in SPSS: visually I can inspect stratified log minus log plots (and scatterplots of residuals for continuous variables). My question is about the statistical method: checking if the product of time and covariate becomes significant in the cox regression (if yes, not fulfilling PH assumption). I havenoticed that it is quite common to first make an univariable cox regression for each covariate. I have been reading on the subject but see that different methods are used when it comes to check individual Time dependent covariates.
Some people check the product of timevariable (T_COV) univariable in the cox-regression, others put both the T_COV and the original variable in the cox regression (example for age: TAge and age would both be taken into the cox-regression). In the second method, one does noet acquire univariable cox regression for the T_COV.
Why is it important to me? There is one T_COV variable for the location of the tumor that is not significant in univariable cox- regression, but becomes significant in the regression with only the T_COV and the original variable that it is a product of (T*tumorlocation).
I hope you want to give me your thoughts on the topic. I am extra happy with reading recommendations/reliable sources! If you have other remarks, questions, or if my methods are all wrong: please comment! Is it helpful if i write down the specific HR's etc?