Dear R users,
I am interested in estimating the effects of a treatment on two
time-to-event traits (on simulated data), accounting for the dependency
between the two time-to-event outcomes.
I precise that the events are NOT recurrent, NOT competitive, NOT ordered.
The individuals are NOT related
t)
> # might want to allow different shapes or scales for different events
> for (k in seq(kk)) {
> short[[paste0("time", k)]] <- rweibullPH(nn, shape=2,
> scale=exp(beta[k]*tx)*gamma)
> }
> # might want to allow censoring
>
> long <- reshape(sho
>
> Dear R help list,
>
> I would like to perform a score test for a subset of the parameters
> estimated with coxph using the frailty() option.
> As illustrated in the following reproducible example, I am able to perform
> the score test with the standard coxph() but not in presence of frailty()
>
0.97060.9958
Iterations: 5 outer, 21 Newton-Raphson
Variance of random effect= 0.001494078 I-likelihood = -711.9
Degrees of freedom for terms= 1.0 1.0 1.0 0.2
Concordance= 0.649 (se = 0.026 )
Likelihood ratio test= 23.22 on 3.21 df, p=4.703e-05
Le jeu. 15 août 2019 à 18:11, Denise b
4 matches
Mail list logo
