R: Cox proportional hazard model - confounding variables

Survival analysis
Title: Interpreting coefficients in a multiple explanatory variable Cox proportional hazard model: confounding variable
Hosmer & Lemeshow Chapter 4

[@lukegaylor2189]

when you calculate the mean across the two groups, we see there is a difference. But if we were to test for significance would one undertake an anova() test?

[@neilnew8354]

you turn the ivhx into a categorical variable by using dat$ivhx[[dat$ivhx>2]= 1 and less than 2 as zero.
Why do you code it this way instead of using methods shown in other videos of cutting it into two equal halves. g= quantile(dat$ivhx,(0:2)/2) then cut(dat$ivhx,g)??? They give you different values on the cox model but I am unsure which one you are supposed to be doing. please help!

[@hull39]

what web site is being referred to in the video?

[@PhilChanstats]

Hi. The website no longer being hosted.