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.
A data frame with 2323 observations on the following 4 variables.
enrolling center, a number from 1 to 37
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
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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