[R] cluster() or frailty() in coxph

[Joshua Wiley]

Hi Ehsan,

My understanding (hopefully someone will jump in if this is wrong) is
that cluster() identifies a variable that is an indicator for
correlated observations (rats in a litter, children in a classroom,
etc.).  The relative risk from treatment (rx) is for a random sample
of rats.

frailty() estimates the relative risk from treatment (rx) within
litters.  Also, by default, it (frailty) uses a gamma distribution and
estimates the scale parameter unless specified by theta (or df).

There is an entire chapter devoted to frailty models in Therneau &
Grambsch book on the cox model (the title is something like Survival
Data Analysis).

HTH,

Josh

On Sat, Jun 25, 2011 at 3:48 PM, Ehsan Karim <wildscop at hotmail.com> wrote:
> Dear List,
>
> Can anyone please explain the difference between cluster() and
> frailty() in a coxph? I am a bit puzzled about it. Would appreciate
> any useful reference or direction.
>
> cheers,
>
> Ehsan
>
>
>
>> marginal.model <- coxph(Surv(time, status) ~ rx + cluster(litter), rats)
>> frailty.model  <- coxph(Surv(time, status) ~ rx + frailty(litter), rats)
>> marginal.model
> Call:
> coxph(formula = Surv(time, status) ~ rx + cluster(litter), data = rats)
>
>
>    coef exp(coef) se(coef) robust se    z      p
> rx 0.905      2.47    0.318     0.303 2.99 0.0028
>
> Likelihood ratio test=7.98  on 1 df, p=0.00474  n= 150
>> frailty.model
> Call:
> coxph(formula = Surv(time, status) ~ rx + frailty(litter), data = rats)
>
>                coef  se(coef) se2   Chisq DF   p
> rx              0.914 0.323    0.319  8.01  1.0 0.0046
> frailty(litter)                      17.69 14.4 0.2400
>
> Iterations: 6 outer, 24 Newton-Raphson
>     Variance of random effect= 0.499   I-likelihood = -180.8
> Degrees of freedom for terms=  1.0 14.4
> Likelihood ratio test=37.6  on 15.4 df, p=0.00124  n= 150
>
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-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/