Hello Dr Balci,
Thanks for the survival module. is it possible to add the proportional hazards assumption check in the Cox model for example with a schoenfel residuals graph.
thanks again
Clinicopath survival
Re: Clinicopath survival
Hi,
Would you please guide me to a literature or R-code for your request.
Thank you
Serdar Balci
Would you please guide me to a literature or R-code for your request.
Thank you
Serdar Balci
Re: Clinicopath survival
Hey Serdar,
you already import R package survival and surminer.
Look in surminer the function:
ggcoxzph(): Graphical test of proportional hazards. Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve using ggplot2. Wrapper around plot.cox.zph().
Also take a look at the screenshot with a few lines of code in the Rj editor. Cheers,
Maurizio
you already import R package survival and surminer.
Look in surminer the function:
ggcoxzph(): Graphical test of proportional hazards. Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve using ggplot2. Wrapper around plot.cox.zph().
Also take a look at the screenshot with a few lines of code in the Rj editor. Cheers,
Maurizio
Re: Clinicopath survival
Hello Dr Balci,
In survminer used by jsurvival :
Diagnostics of Cox Model :
ggcoxzph(): Graphical test of proportional hazards. Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve using ggplot2. Wrapper around
plot.cox.zph().
ggcoxdiagnostics(): Displays diagnostics graphs presenting goodness of Cox Proportional Hazards Model fit.
ggcoxfunctional(): Displays graphs of continuous explanatory variable against martingale residuals of null cox proportional hazards model. It helps to properly choose the functional form of continuous variable in cox model.
Thank
In survminer used by jsurvival :
Diagnostics of Cox Model :
ggcoxzph(): Graphical test of proportional hazards. Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve using ggplot2. Wrapper around
plot.cox.zph().
ggcoxdiagnostics(): Displays diagnostics graphs presenting goodness of Cox Proportional Hazards Model fit.
ggcoxfunctional(): Displays graphs of continuous explanatory variable against martingale residuals of null cox proportional hazards model. It helps to properly choose the functional form of continuous variable in cox model.
Thank
Re: Clinicopath survival
Thank you.
So they seem to be easily implementable.
I will work on them
So they seem to be easily implementable.
I will work on them

Re: Clinicopath survival
Hello Dr Balci,
something new for the proportional hazards assumption check in the Cox model?
https://github.com/sbalci/jsurvival/issues/3
Thank
something new for the proportional hazards assumption check in the Cox model?
https://github.com/sbalci/jsurvival/issues/3
Thank
Re: Clinicopath survival
I am working on it, the functions are being rewritten due to some bugs.
The modules will be updated in upcoming weeks.
The modules will be updated in upcoming weeks.