# How to handle non-proportional hazards when you have multiple groups and differences in event rate based on study design

I am looking at time-to-event data by a variable with multiple groups (8). When I plot the stratified KM, some curves cross, some are ok, and some diverge. Also, I'm interested in the 30-day event rate. But by definition, I dont start to count events until after 7 days (only if there is a death I count those, so I may have a tiny drop in the first 7 days). What is the best way to approach this analysis for KM and for Cox?

• What does it mean that a KM curve "diverges"? You mean do not appear proportional with the other groups? Commented Jul 10, 2023 at 18:10
• Yes, not proportional over time so earlier times closer together and then later times appear farther away Commented Jul 10, 2023 at 19:08
• It's hard to see proportionality on the survival scale - "earlier times closer together and then later times appear farther away" - is actually a perfect description of parallel hazard functions. Try plotting those curves on complementary log log scales to see if the hazard is actually parallel. Commented Jul 10, 2023 at 19:38
• I plotted as you suggested. It is definitely not parallel. Commented Jul 10, 2023 at 21:20
• Some of my stratas are quite small (11 patients) which may also be a problem Commented Jul 10, 2023 at 21:26

A "parametric" check for disproportional hazards is provided by the R-function cox.zph from the survival-package. See here: https://stats.stackexchange.com/a/318319/341520