Re: st: Main effect for time-varying covariate

[Steve Samuels <sjsamuels@gmail.com>]

Nichole:

Please explain what the risk factor is and how its activation depends on the medical records. Perhaps you mean that the presence of the risk factor is known only after some test, and that test is recorded in the records. If so, the fact that the test is made at time "t" doesn't preclude the presence of the factor before "t". Also, if the test was made in response to certain symptoms, then other issues arise.

Steve


On Aug 27, 2013, at 5:00 PM, Boyle, Nicole M wrote:

Hi Steve,

Thanks for your response! I've elaborated on the issue in more (perhaps excessive) detail:


***Variable details***
I'd like to model a binary variable as time-varying. This binary variable will model the onset of a particular
risk factor. All patients under study enter into the study with this risk factor "turned off." The timing of
when this risk factor "turns on" depends entirely on each patient's medical records (and for some patients,
this risk factor may never "turn on"). This risk factor can only go from "off" to "on"; the reverse ("on" to "off")
is not possible.


***Reason for modeling this var as time-varying***
I would like to model this particular risk factor as a time-varying covariate in order to assess its association
with the outcome while avoiding possible immortal time bias. In other words, I'd like assess the hazard ratio
(at any instantaneous time during observation) for the outcome event comparing those with the risk factor
"turned on" vs. those with the risk factor "turned off", accounting for the possibility that a patient's risk factor
may be "turned on" at any time before or after his/her outcome event.


***Stata's covariate vs. coefficient distinction***
Right now, the closest I can find to an answer is a mention in the Stata Statistical Analysis Manual:

         http://www.stata.com/manuals13/ststcox.pdf#ststcoxRemarksandexamples

In said manual, Cox models are run with and without the time-invariant component (on page 12 and pages 
13-14, respectively). The Stata manual differentiates between models fit with time-varying COVARIATES
(without the time-invariant component) from models fit with time-varying COEFFICIENTS (with the time-invariant
component), saying 

       "Above we used tvc() and texp() to demonstrate fitting models with time-varying covariates, but
        these options can also be used to fit models with time-varying coefficients."

I think this aforementioned covariate/coefficient distinction may be the source of my confusion. From the
manual's suggestion, it seems like adding this time-invariant component (aka: "main effect") will only test 
the proportional hazards assumption of the coefficient.


Thanks,
Nicole
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Steve Samuels [sjsamuels@gmail.com]
Sent: Wednesday, August 21, 2013 2:13 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Main effect for time-varying covariate

I'd need to know details about the internal covariate before I can
answer your question. So please describe what it is and how its values
are determined.

Steve

On Aug 20, 2013, at 7:14 PM, Boyle, Nicole M wrote:

Hi all,

I'm modeling a multivariable competing risks regression model (stcrreg), and I want to include an internal
time-varying covariate.

(1) Should I include a main effect for this time-varying covariate in the model? (I'm not trying to test
the proportionality assumption here)

(2) How does one report the overall value and significance of this time-varying variable?

Thanks,
Nicole

(my apologies if this is a duplicate... 1st email bounced)
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