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This is a simulated surival data set for investigating random center effects. To make it realistic, the number of centers and their sizes is based on an EORTC cancer trial.

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A data frame with 2323 observations on the following 4 variables.

`y`

survival time

`uncens`

0=alive, 1=dead

`center`

enrolling center, a number from 1 to 37

`trt`

treatment arm, 0 or 1

This is used in the test suite for the code.

PhD thesis work of Jose Cortinas Abrahantes

Cortinas Abrahantes, Jose; Burzykowski, Tomasz (2002), A version of the EM algorithm for proportional hazards models with random effects , Published in: Lecture Notes of the ICB Seminars. p. 15-20

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```
Loading required package: survival
Loading required package: bdsmatrix
Attaching package: 'bdsmatrix'
The following object is masked from 'package:base':
backsolve
Cox mixed-effects model fit by maximum likelihood
Data: eortc
events, n = 1463, 2323
Iterations= 5 28
NULL Integrated Fitted
Log-likelihood -5609.797 -5539.43 -5528.94
Chisq df p AIC BIC
Integrated loglik 140.74 2.00 0 136.74 126.16
Penalized loglik 161.72 10.22 0 141.28 87.25
Model: Surv(y, uncens) ~ trt + (trt | center) + strata(center)
Fixed coefficients
coef exp(coef) se(coef) z p
trt 0.7431879 2.102628 0.0784898 9.47 0
Random effects
Group Variable Std Dev Variance
center trt 0.24220971 0.05866554
```

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