Cox proportional hazards

[#1]

Hi!

I am very new to this forum and to JMP&statistics in general. I would appreciate if somebody could advise me on a following issue:

I am analyzing whether certain factors (A, B, C etc - all of them are continuous variables) are predictors of a disease (X) incidence. I have 2 independent groups of patients (group 1 - healthy, and group 2 - those ended up with a disease). I need to adjust those factors for age, gender, race etc. When I go to Analyze->Reliability and Survival->Fit Proportional hazards I am a little bit puzzled what goes where. Could you please advise?

I apologize those of you who will see this question as a very basic one. I was trying to look it up online but could not fins a definite answer anywhere

I will greatly appreciate your help!

Casandra

[#2 · Accepted solution]

In this Mastering JMP WebEx, I showed how to fit a Cox's PH model to the data similar to yours. This is the link to the recordings: Advanced Mastering JMP: Analyzing Survival Data | JMP

Hope it helps.

[#3]

Hi Jian

Does Jmp pro 13.2 have the option for time-dependent or time-varying covariates. I tried to find some info but I could not.

Hope you can shed more light on my question

Thank you

Chris

[#4]

Hi. The Advanced Mastering session was out of date and no longer avaialble.  Perhaps these video will help: 

Survival Analysis in Biostatistics

 JMP Academic Webinar – Teaching Survival and Reliability Analysis with JMP

[#5]

It may be that the proportional hazards is not the appropriate approach here. You should learn from the Mastering webex that this method is for when you have a time-to-event outcome, such as time-to-death. These methods also deal with censoring. For example, where you have subjects at the end of the observed time period who have still not experienced the event.

It sounds like in your situation all you know about the outcome for the subject is a binary: healthy or with-disease (1 / 2). So this would be handled with a logistic regression.

[#6]

I used the Cox Proportional Hazards model a few years ago and was not familiar with it at the time. I wondered about what was actually being assumed in that model - I wanted an intuitive understanding of what that model assumed, not just a mathematical statement of the assumptions. I could not find one at the time. But, I got one recently from AI - not just the intuition, but a graph illustrating how close (or not) my particular case was to what that model was assuming.  This is an area where AI really helps. My experience has been that questions like this allow AI to operate like a colleague who knows more than I do and can explain things in ways that allow me to learn. Miraculous in my mind, despite all the dangers it poses to everything.