Displaying 5 results from an estimated 5 matches for "coxpenal".
2004 Nov 17
1
frailty and time-dependent covariate
...ed to my data.
Thanks a lot
Emanuela Rossi
> fit_19_1<-coxph(Surv(DATA_INI1,DATA_FIN1,EVENT1)~ V1+V2+alt1+alt2+strata(autocorr1)+cap1+SP+SP2+SP3+SP3:log(DATA_FIN1)+D1500+D3000+D4500+frailty.gaussian(ID),data=SURV1)
Warning messages:
1: Inner loop failed to coverge for iterations 1 3 in: coxpenal.fit(X, Y, strats, offset, init = init, control, weights = weights,
2: longer object length
is not a multiple of shorter object length in: offset + coxfit$fcoef[x[, fcol]]
3: X matrix deemed to be singular; variable 8 in: coxph(Surv(DATA_INI1, DATA_FIN1, EVENT1) ~ V1 + V2 + alt1 + alt2 +...
2002 Oct 08
2
Frailty and coxph
...--------------------------
the result is 'NULL', but with 'real data', I usually get the predicted
frailties. The help pages doesn't even mention the component 'frail', but
in the code I can see that 'frail' is reurned if 'nfrail > 0'. And
(from 'coxpenal.fit.s'):
---------------------------
if (any(sparse)) {
...
}else{
nfrail <- 0
...
}
---------------------------
and
---------------------------
sparse <- sapply(pattr, function(x) !is.null(x$sparse) && x$sparse)
---------------------------
but here I lose...
2008 Jan 16
1
exact method in coxph
I'm trying to estimate a cox proportional hazards regression for repeated
events (in gap time) with time varying covariates. The dataset consists of
just around 6000 observations (lines) (110 events).
The (stylized) data look as follows:
unit dur0 dur1 eventn event ongoing x
1 0 1 0 0 0 32.23
1 1 2 0 1 1 35.34
1
2001 Nov 12
2
check() warnings for survival-2.6
...uot;
[7] "[.terms" "anova.survreg"
[9] "anova.survreglist" "as.character.Surv"
[11] "as.data.frame.Surv" "as.data.frame.difftime"
[13] "as.matrix.ratetable" "coxpenal.fit"
[15] "format.Surv" "is.category"
[17] "is.na.Surv" "is.na.coxph.penalty"
[19] "is.na.ratetable" "is.na.ratetable2"
[21] "labels.survreg" "...
2006 Sep 19
0
How to interpret these results from a simple gamma-frailty model
..."Theta= 100 org beta 0.4284 M1: 0.467735 M2: 0.48221"
[6] "Theta= 100 org beta 0.5234 M1: 0.673852 M2: 0.683147"
[1] "Theta = 100 proportion pred. M2 more accurate than M1 = 0.564"
Warning message:
Inner loop failed to coverge for iterations 2 3 in: coxpenal.fit(X, Y, strats, offset, init = init, control, weights = weights,
>
I don't understand the following:
[1] The variance of the estimated individual frailty values is always much lower than both the original variance and the estimated variance of the random effect. Why is this ? Obviously...