Thank you very much for responding. Yes, I incorrectly stated that
frailtypack was the only widely available software for the analysis of
nested frailty models. When I initially began my search to identify
software well suited to nested frailty analysis, Frailtypack dominated the
google results. While this package seems to be widely publicized on the
internet, I have not thus far found it to be well suited to analysis with my
large dataset.
I would like to use coxme to analyze my data, as it appears to have far
fewer idiosyncrasies than Frailtypack. However, at the moment I am
struggling to 1) achieve model convergence with even a basic shared frailty
model and 2) produce the correct code for the nested frailty model. My
dataset involves recurrent events clustered within individuals (ID) and
individuals then clustered within groups of three (GroupNum). One
independent variable (Alcohol) varies by group and another (Gender) varies
by individual. I ultimately aim to produce a nested frailty model that
includes one random intercept variance term at the level of the individual
and one at the level of the group. I have already produced results for a
basic shared frailty model using SAS NLMIXED--a model that accounts for
clustering only at the level of the Group using group-level predictors
(Alcohol)--but so far I have not been able to achieve convergence for this
same model using coxme. I suspect that supplying the program with starting
values might be useful, but I am not familiar enough with the program code
to do so. Any suggestions would be very much appreciated. I am new to
survival analysis as well as the R software program.
##Basic Shared Frailty Model
> cgd.nfm <- coxme(Surv(Duration, Censoring) ~ Alcohol + (1 | ID),
> data=mydata)
> summary(cgd.nfm)
Length Class Mode
coefficients 1 -none- numeric
frail 1 -none- list
penalty 1 -none- numeric
loglik 3 -none- numeric
variance 1 bdsmatrix S4
df 2 -none- numeric
hmat 1 gchol.bdsmatrix S4
iter 2 -none- numeric
control 9 -none- list
u 709 -none- numeric
means 1 -none- numeric
scale 1 -none- numeric
linear.predictor 15831 -none- numeric
vcoef 1 -none- list
n 2 -none- numeric
terms 3 terms call
formulaList 2 -none- list
y 31662 Surv numeric
call 3 -none- call
ties 1 -none- character
Nested Frailty Model
> cgd.nfm <- coxme(Surv(Duration, Censoring) ~ Alcohol*Gender + (1 |
> GroupNum/ID), data=mydata)
> summary(cgd.nfm)
Length Class Mode
coefficients 1 -none- numeric
frail 2 -none- list
penalty 1 -none- numeric
loglik 3 -none- numeric
variance 1 bdsmatrix S4
df 2 -none- numeric
hmat 1 gchol.bdsmatrix S4
iter 2 -none- numeric
control 9 -none- list
u 947 -none- numeric
means 1 -none- numeric
scale 1 -none- numeric
linear.predictor 15831 -none- numeric
vcoef 2 -none- list
n 2 -none- numeric
terms 3 terms call
formulaList 2 -none- list
y 31662 Surv numeric
call 3 -none- call
ties 1 -none- character
Terry Therneau-2 wrote
> I can't comment on frailtypack issues, but would like to mention that
> coxme will handle
> nested models, contrary to the statement below that "frailtypack is
> perhaps the only ....
> for nested survival data".
> To reprise the original post's model
>
> cgd.nfm <- coxme(Surv(Tstart, Tstop, Status) ~ Treatment + (1 |
> Center/ID), data=cgd.ag)
>
>
> And a note to the poster-- you should reprise the original message to
> which you are
> responding.
>
>
> Terry Therneau
>
> On 10/09/2013 05:00 AM,
> r-help-request@
> wrote:
>> Hello,
>>
>> I am encountering very similar problems with frailtypack (only, it seems,
>> 3
>> years later). I would be incredibly grateful if you would be willing to
>> share any solutions you happened upon for the problem you mention. I have
>> a
>> datafile that is even longer than yours (over 15000 events). Events
>> follow a
>> two-level nesting structure. When I attempt to run the nested survival
>> model
>> in frailtypack the program either stops running entirely or produces an
>> error message. I have contacted the frailtypack maintainer but have not
>> yet
>> received a response. It seems that frailtypack is perhaps the only
>> widely-available platform for the analysis of nested survival data, so
>> the
>> seeming bugginess of this program is troubling. Please let me know if
>> you
>> ended up coming up with a solution to your problem or, alternatively,
>> another program able to run the nested analysis. Thank you so much!
>>
>
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