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Re: st: Fw: subgroups in cox regression
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: Fw: subgroups in cox regression
Date
Sun, 1 May 2011 10:32:59 -0400
Sorry- ignore the snipped 'There is no "lik" at the end.
Steve
On May 1, 2011, at 10:19 AM, Steven Samuels wrote:
Catherine:
Effect modification means that the coefficient the exposure might differ between stages. To test it, you add an interaction or test for an interaction. One consequence of using the -if- statement is that it doesn't isolate a differential effect of your exposure variable, because all components of the model differ: 1) the baseline hazard; 2) the coefficient for race; and 3) the coefficient for your exposure. This is certainly a possible model and it is a good idea to check for proportionality of the baseline hazard by stage and race by using the strata() option in Stata. I'm also wondering whether you have checked that a linear term in your exposure variable is adequate; you can use the -fracpoly- command to find out. There is no "lik
******************************************
// If you have Stata Version < 11 (I presume so, since you use -xi-
xi: stcox i.race i.stage*igf
// Otherwise with Stata 11
stcox i.race c.igf##i.stage // add ", robust" to get robust standard error
//The interaction term estimates the difference in igf slopes between the two stages.
// You can get the slopes directly by:
tab stage, gen(stage) // create indicators stage1 stage2
gen igf1= igf*stage1
gen igf2= igf*stage2
xi: stcox i.race stage1 igf1 stage2 igf2, nocons
lincom igf1 - igf2 // estimate and test differences with Wald test
****************************
Steve
[email protected]
On Apr 30, 2011, at 10:40 PM, catherine duggan wrote:
Hello
I have what is probably a basic question, which is currently defeating me.
I have run Cox regression with death as my outcome: my main exposure of interest
is a a continuous variable (IGF)
I have other covariates in the model - I will just refer to two of them, race (5
level) and tumor stage (2 level)
Xi: stcox igf i.race i.stage
I did the main analysis, and then did some exploratory subgroup analysis, with
the usual caveats of smaller sample sizes and using a more conservative P value
Eg
Xi: stcox igf i.race if stage==1
However a reviewer gave the comment
' what you might want to do is to construct a model for effect modification -
that is compare the model with no subgroup to one with trends fit for each
subgroup - a 1 dgree of freedom likelihood ratio test - do see if the trends
differ statistically - a test for homogeneity of trends. This would be more
informative'
Unfortunately I have no idea how to accomplish this - I wasn't sure whether this
was a test for interaction or not.
I'd appreciate any guidance
Many thanks
Catherine
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