coxre {event} | R Documentation |
coxre
fits a Cox proportional hazards model to event history
data using a gamma distribution random effect. The parameter, gamma,
is the variance of this mixing distribution.
If a matrix of response times is supplied, the model can be stratified by columns, i.e. a different intensity function is fitted for each column. To fit identical intensity functions to all response types, give the times as a vector.
coxre(response, censor, nest=NULL, cov=NULL, stratified=FALSE, cumul=FALSE,estimate=1, iter=10, print.level=0, ndigit=10, gradtol=0.00001, steptol=0.00001, iterlim=100, fscale=1, typsiz=abs(estimate), stepmax=estimate)
response |
Vector or matrix of times to events, with one column per type of response (or subunit). |
censor |
Corresponding vector or matrix of censoring indicators. If NULL all values are set to one. |
nest |
Vector indicating to which unit each observation belongs. |
cov |
One covariate |
stratified |
If TRUE, a model stratified on type of response (the columns of response) is fitted instead of proportional intensities. |
cumul |
Set to TRUE if response times are from a common origin instead of times to (or between) events. |
estimate |
Initial estimate of the frailty parameter. |
iter |
Maximum number of iterations allowed for the inner EM loop. |
others |
Plotting control options. |
D.G. Clayton and J.K. Lindsey
Clayton, D. (1987) The analysis of event history data: a review of progress and outstanding problems. Statistics in Medicine 7: 819-841
# 11 individuals, each with 5 responses y <- matrix(c(51,36,50,35,42, 27,20,26,17,27, 37,22,41,37,30, 42,36,32,34,27, 27,18,33,14,29, 43,32,43,35,40, 41,22,36,25,38, 38,21,31,20,16, 36,23,27,25,28, 26,31,31,32,36, 29,20,25,26,25),ncol=5,byrow=TRUE) # Different intensity functions coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, est=0.7, stratified=TRUE) # Proportional intensity functions for the five responses coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, est=0.7, stratified=FALSE) # Identical intensity functions coxre(response=as.vector(t(y)), censor=rep(1,55), nest=rep(1:11,rep(5,11)), est=0.7)