You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Distriburted Research Network does not gather the whole statistical attributes, so a researcher cannot know if there was important violation of proportional hazard assumption, which may lead to wrong and misleading estimates ref.
Should we add 'assumption test' for Cox Hazard model, whose result a researcher can gather, too?
The text was updated successfully, but these errors were encountered:
Schoenfeld $r_ij$ residuals for failure $i$ and covariate $j$ may not be terribly effective as plotting $r_ij$ as a function of covariate $j$ should be centered about 0. However, we only have two discrete values for covariate $j$ (the treatment effect), so this may be hard to see. The alternative is to plot as a function of failure time.
One will need to port the code from cox.zph() into CohortMethod or Cyclops
Another approach is to plot log(-log(S(t))) where S(t) is the survival function estimate that Cyclops (already? I believe) provides.
S(t) is also approximated into the Kaplan-Meier plots that we have already generated and packaged up across data sources. @chandryou -- maybe this is the way you want to go in your ACS study?
BTW, the formula for the Schoenfeld residuals is super-simple for a binary covariate and a time-invariant model with Breslow-like ties (which we are using):
Distriburted Research Network does not gather the whole statistical attributes, so a researcher cannot know if there was important violation of proportional hazard assumption, which may lead to wrong and misleading estimates ref.
Should we add 'assumption test' for Cox Hazard model, whose result a researcher can gather, too?
The text was updated successfully, but these errors were encountered: