Is there a way to check that the proportional hazards assumption is correct for a Cox model with time-varying covariates ?
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3 Answers
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If we add time-dependent covariates or interactions with time to the Cox proportional hazards model, then it is not a “proportional hazards” model any longer.
See this presentation: http://ms.uky.edu/~mai/sta635/Cox%20model.pdf
or this lecture notes: http://www.math.ucsd.edu/~rxu/math284/slect7.pdf
But this is a widely known feature.
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The answer of Serpico is true for time-dependent coefficients but not if the model uses time-dependant covariates. If this was the case, I don't know the correct answer.
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1$\begingroup$ This is a confusing answer. $\endgroup$ Commented Oct 9, 2017 at 14:16
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$\begingroup$ Time-dependent covariates are measured values that change along the study. Time-dependents coefficients imply that some $\beta$ is not constant across time. Philosophically speaking, there's not much difference - since I guess there's always a way to convert between products $\beta(t) x $ and $ \beta x(t)$, if we can choose any shape of time-dependency. $\endgroup$– juodCommented Oct 9, 2017 at 16:23
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$\begingroup$ @juod Your comment would therefore indicate that we must not verify the proportional hazards assumption with a model with time-dependent covariates. However, the answer for this question: stats.stackexchange.com/questions/246488/… appears to indicate otherwise $\endgroup$ Commented Oct 9, 2017 at 16:49
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1$\begingroup$ @Emmanuel.W I agree with you that such a model still assumes proportional hazards given same covariate levels. I was referring to the discrepancy between your answer and Serpico's references - they say that the term $\beta x t$ has a time-dependent covariate, while I'd say it's the coefficient that is time-dependent there. $\endgroup$– juodCommented Oct 10, 2017 at 8:06
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As Serpico suggests, the Cox model with time-dependent covariates is no longer a proportional hazards model. Here is a quote from David Collett's book, Modelling Survival Data in Medical Research (2nd ed., 2003, p. 253), that may provide some further clarification:
It is important to note that in the model given in equation $h_i(t) = \exp \left\{ \sum_{j=1}^p \beta_j x_{ji}(t) \right\} h_o(t)$, the values of the variables $x_{ji}(t)$ depend on the time $t$, and so the relative hazard $h_i(t)/h_0(t)$ is also time-dependent. This means that the hazard of death at time $t$ is no longer proportional to the baseline hazard, and the model is no longer a proportional hazards model.
