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I'm using the smoothed scaled Schoenfeld residual plot to assess the proportional hazard assumption. I have a decent understanding of what a smoothed scaled Schoenfeld residual plot shows, but I'm still a bit confused about some details. Where exactly should the line be for assuming that the proportional hazard assumption is not violated? I previously read on Stack Exchange that I should look for an almost flat smoothed curve that doesn't deviate much from the coxph() coefficient value.

However, I've also been told that the line should be close to 0, as the test of correlation between the Schoenfeld residuals and survival time should be zero (the null hypothesis), indicating that the proportional hazard assumption is not violated. I hope someone can elaborate.

Thanks in advance!

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Although it's called a "scaled Schoenfeld residuals plot," for each predictor variable it's really a plot of the sum of those residuals plus the (constant) log-hazard ratio reported by the model. That's explained toward the middle of this answer. The plot is often accompanied by a smoothed interpolation (loess) of those "residuals," which is what you want to be reasonably flat. Remember that for correlations you first subtract the mean from all the individual values anyway, so the constant offset due to adding in the log-hazard ratio doesn't matter. Also, newer versions of the R survival package no longer use the correlation per se in cox.zph(); it's been replaced by a score test. See this answer.

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  • $\begingroup$ Please correct me if I'm wrong, but what I understand from your answer and the provided links, is that the smoothed line represents the trend of the residuals over time, and if the smoothed line is around the log-hazard ratio on the y-axis, then it indicates that the proportional hazard assumption is not violated. This is because that the cox.zph() argument uses an exact score test, instead of testing the correlation between the Schoenfeld residuals and survival time, that should be around zero. Is this correct? @EdM $\endgroup$
    – Devi Sita
    Commented Jun 2 at 19:41
  • $\begingroup$ One more thing, I also start to wonder, what if plotting the hazard ratio estimates directly over time instead of examining the residuals over time, would that be better? In other words, why look at the residual plot to assess the proportional hazard assumption? Why not look at the hazard ratio estimate over time to asses the PH assumption? @EdM $\endgroup$
    – Devi Sita
    Commented Jun 3 at 12:44
  • $\begingroup$ @DeviSita the smoothed plot of residuals around the overall log-hazard ratio IS an estimate of the hazard ratio over time, to my knowledge the best anyone has come up with. See the explanation and equation in this answer. $\endgroup$
    – EdM
    Commented Jun 3 at 13:52
  • $\begingroup$ Thanks for your help! @EdM $\endgroup$
    – Devi Sita
    Commented Jun 3 at 22:04

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