I am building a cox survival analysis model with a retailer's transaction data. Almost all the variables have failed the proportionality test. Can I continue with the Cox model? Should I build a LIFEREG model instead of the Cox model?
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1$\begingroup$ LIFEREG is not the name of a model. Don't think of SAS as life. Are the predictors such that they should have a constant effect over time? If they have a diminishing effect over time you might go with an accelerated failure time model such as log-logistic or log-Gaussian. $\endgroup$– Frank HarrellCommented Jan 29, 2014 at 23:25
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$\begingroup$ Sorry about that.I meant Parametric models. I created time dependent variables ( model variables*log(time)) and these time dependent variables were significant. I even examined Schoenfeld Residuals to confirm and all the variables failed the test. I think I will try Parametric models. I was just concerned that how can all the variables fail the test. $\endgroup$– NewguyCommented Jan 30, 2014 at 18:07
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$\begingroup$ Make sure you used the time-dependent special likelihood; you can't use add product terms (with time) in the model. I recommend fitting a couple of accelerated failure time models and plotting the Kaplan-Meier estimate of the distribution of the right-censored residuals to check agreement against the assumed distribution. $\endgroup$– Frank HarrellCommented Jan 30, 2014 at 22:53
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