Survival Analysis Using SAS®: A Practical Guide

Conclusion

It’s no accident that Cox regression has become the overwhelmingly favored method for doing regression analysis of survival data. It makes no assumptions about the shape of the distribution of survival times; it allows for time-dependent covariates; it is appropriate for both discrete-time and continuous-time data; it easily handles left truncation; it can stratify on categorical control variables; and it can be extended to nonproportional hazards. The principal disadvantage is that you lose the ability to test hypotheses about the shape of the hazard function. As we’ll see in Chapter 8, however, the hazard function is often so confounded with unobserved heterogeneity that it’s difficult to draw any substantive conclusion from the ...