[R] What's the baseline model when using coxph with factor variables?
Andreas Schlicker
a.schlicker at nki.nl
Fri Dec 2 09:03:23 CET 2011
William and David, thanks for your help.
The contrasts option was indeed what I was looking for but didn't find.
andi
On 01.12.2011 20:56, David Winsemius wrote:
>
> On Dec 1, 2011, at 1:00 PM, William Dunlap wrote:
>
>> Terry will correct me if I'm wrong, but I don't think the
>> answer to this question is specific to the coxph function.
>
> It depends on our interpretation of the questioner's intent. My answer
> was predicated on the assumption that the phrase "baseline model"
> meant baseline survival function, ... S_0(t) in survival analysis
> notation.
>
>
>> For all the [well-written] formula-based modelling functions
>> (essentially, those that call model.frame and model.matrix to
>> interpret
>> the formula) the option "contrasts" controls how factor
>> variables are parameterized in the model matrix. contr.treatment
>> makes the baseline the first factor level, contr.SAS makes
>> the baseline the last, contr.sum makes the baseline the mean,
>> etc. E.g.,
>>
>>> df<- data.frame(time=sin(1:20)+2,
>> cens=rep(c(0,0,1), len=20),
>> var1=factor(rep(0:1, each=10)),
>> var2=factor(rep(0:1, 10)))
>>> options(contrasts=c("contr.treatment", "contr.treatment"))
>>> coxph(Surv(time, cens) ~ var1 + var2, data=df)
>> Call:
>> coxph(formula = Surv(time, cens) ~ var1 + var2, data = df)
>>
>>
>> coef exp(coef) se(coef) z p
>> var11 0.1640 1.18 0.822 0.1995 0.84
>> var21 0.0806 1.08 0.830 0.0971 0.92
>>
>> Likelihood ratio test=0.05 on 2 df, p=0.974 n= 20, number of
>> events= 6
>>> options(contrasts=c("contr.SAS", "contr.SAS"))
>>> coxph(Surv(time, cens) ~ var1 + var2, data=df)
>> Call:
>> coxph(formula = Surv(time, cens) ~ var1 + var2, data = df)
>>
>>
>> coef exp(coef) se(coef) z p
>> var10 -0.1640 0.849 0.822 -0.1995 0.84
>> var20 -0.0806 0.923 0.830 -0.0971 0.92
>>
>> Likelihood ratio test=0.05 on 2 df, p=0.974 n= 20, number of
>> events= 6
>>> options(contrasts=c("contr.sum", "contr.sum"))
>>> coxph(Surv(time, cens) ~ var1 + var2, data=df)
>> Call:
>> coxph(formula = Surv(time, cens) ~ var1 + var2, data = df)
>>
>>
>> coef exp(coef) se(coef) z p
>> var11 -0.0820 0.921 0.411 -0.1995 0.84
>> var21 -0.0403 0.960 0.415 -0.0971 0.92
>>
>> Likelihood ratio test=0.05 on 2 df, p=0.974 n= 20, number of
>> events= 6
>>
>> (lm() has a contrasts argument that can override
>> getOption("contrasts")
>> and set different contrasts for each variable but coxph() does not
>> have
>> that argument.)
>>
>> Bill Dunlap
>> Spotfire, TIBCO Software
>> wdunlap tibco.com
>>
>>> -----Original Message-----
>>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org
>>> ] On Behalf Of David Winsemius
>>> Sent: Thursday, December 01, 2011 9:36 AM
>>> To: a.schlicker at nki.nl
>>> Cc: r-help at r-project.org
>>> Subject: Re: [R] What's the baseline model when using coxph with
>>> factor variables?
>>>
>>>
>>> On Dec 1, 2011, at 12:00 PM, Andreas Schlicker wrote:
>>>
>>>> Hi all,
>>>>
>>>> I'm trying to fit a Cox regression model with two factor variables
>>>> but have some problems with the interpretation of the results.
>>>> Considering the following model, where var1 and var2 can assume
>>>> value 0 and 1:
>>>>
>>>> coxph(Surv(time, cens) ~ factor(var1) * factor(var2), data=temp)
>>>>
>>>> What is the baseline model? Is that considering the whole population
>>>> or the case when both var1 and var2 = 0?
>>>
>>> This has been discussed several times in the past on rhelp. My
>>> suggestion would be to search your favorite rhelp archive using
>>> "baseline hazard Therneau", since Terry Therneau is the author of
>>> survival. (The answer is closer to the first than to the second.)
>>>
>>>>
>>>> Kind regards,
>>>> andi
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>> David Winsemius, MD
>>> West Hartford, CT
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>
> David Winsemius, MD
> West Hartford, CT
>
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