Charles C. Berry wrote: > On Sat, 8 Dec 2007, Charles C. Berry wrote: > >> Gad Abraham <g.abraham <at> ms.unimelb.edu.au> writes: >> >>> Hi, >>> >>> I'm using natural cubic splines from splines::ns() in survival >>> regression (regressing inter-arrival times of patients to a queue on >>> queue size). The queue size fluctuates between 3600 and 3900. >>> >>> I would like to be able to run predict.survreg() for sizes <3600 and >>>> 3900 by assuming that the rate for <3600 is the same as for 3600 and >>> that for >4000 it's the same as for 4000 (i.e., keep the splines cubic >>> within the boundaries but make them constant outside the boundaries). >>> >> [snip] >> >>> Any suggestions? >> Here is one. >> >>> range(ovarian$age) >> [1] 38.8932 74.5041 >>> trim <- function(x) pmin(74.5041 ,pmax(38.8932 , x)) >>> s <- survreg(Surv(futime, fustat) ~ ns(age, knots=c(50, >> 60),Boundary.knots=c(38.8932, 74.5041)),data=ovarian) >>> s2 <- survreg(Surv(futime, fustat) ~ ns(trim(age), knots=c(50, >> 60),Boundary.knots=c(38.8932, 74.5041)),data=ovarian) > > Should have copy-and-pasted this here: > > newage <- data.frame( age=seq(10,200,10 ) ) > >>> matplot(newage, cbind(predict(s,newdata=newage),predict(s2,newdata=newage)))
Thanks Chuck, that works nicely. Cheers, Gad -- Gad Abraham Department of Mathematics and Statistics The University of Melbourne Parkville 3010, Victoria, Australia email: [EMAIL PROTECTED] web: http://www.ms.unimelb.edu.au/~gabraham -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.