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(repsonse, censor, nest, cov, stratified=F, cumul=F, 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. |
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. |
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(rweibull(55,2,5),ncol=5) # Different intensity functions coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, est=0.7, stratified=T) # Proportional intensity functions coxre(response=y, censor=matrix(rep(1,55),ncol=5), nest=1:11, cov=rpois(11,2), est=0.7, stratified=F) # Identical intensity functions coxre(response=as.vector(t(y)), censor=rep(1,55), nest=rep(1:11,rep(5,11)), est=0.7)