# How to correctly interpret Schoenfeld Residuals P-Value

I have been reading various responses on this topic but I do not yet understand how the p-value is interpreted to determine if the proportional hazards assumption holds or not.

I have a global p-value of 0.0506 with all features having p-values >0.1. My understanding of the null hypothesis is that the proportional hazards assumption holds if the p-value is <0.05 but if the p-value is larger than 0.05 then it should mean that there is not enough evidence to reject the null hypothesis and this does not mean that the PH Assumption Holds or we should accept the Null. But in most responses, it seems to suggest that if the p-value is not significant then the proportional hazards hold? Using the inference test via Schoenfeld residuals shows all the variables being not flat around the 0 line.

If the global p-value is significant then the PH assumption does not hold for the model. Schoenfeld is like a Shapiro-Wilk test of normality, if $$p<0.05$$ then the feature is not normally distributed. If Schoenfeld $$p<0.05$$, then the model or feature does not meet the PH assumption. You would need the global p-value to not be less than 0.05 before you start dipping into the individual feature p-values.