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I would like to implement the time-varying coefficients model (cf. Fan and Zhang, 1999) for a Cox proportional hazards model, as proposed by Cai and Sun (2003), and studied by Tian, Zucker and Wei (2005).

This is a somewhat under-appreciated approach to a basic problem. There are commonly used related methods, such as in base R survival that make parametric assumptions on the form of the time-varying coefficients. By contrast I am looking for a local smoothing approach to the estimating equation.

I would like to know if there is a publicly available implementation, particularly for R. If not I would like advice to implement the method. Do I need to start from scratch or can I simply start from the output of standard Cox software such as coxph which gives the gradient, hessian, and allows subject specific weights?

Alexis
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user36302
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    Note that this question is not about programming, debugging or help with using the R language. Cross Validated is the right forum since I need an expert in varying coefficients models to suggest an approach to implementation, while checking if one already exists. – user36302 May 15 '18 at 19:34

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