[R] Meaning of pterms in survreg object?

Johannes Huesing johannes at huesing.name
Fri Jan 28 22:25:00 CET 2011

Johannes Huesing <johannes at huesing.name> [Mon, Jan 10, 2011 at 09:26:37PM CET]:
> I am trying to model survival data with a Weibull distribution                                                                         
> using survreg. Units are clustered two apiece, sometimes receiving                                                                     
> the same treatment and sometimes opposing treatment.                                                                                   
> Residual and predict methods are not carried out on the survreg                                                                        
> object, although the component linear.predictors exists for the                                                                        
> survreg object. Looking at the code I see that the residual method                                                                     
> refuses to run if any of the components of the pterms vector is                                                                        
> equal to 2.                                                                                                                            
> When taking the logarithm of the data and trying a linear mixed                                                                        
> model, residuals and predicted values are produced just fine.                                                                          
> So what is pterms and why is it that, when any component of it                                                                         
> is 2, residuals are not allowed to be displayed?     

I am using R 2.10.1, and here is some example code:

anzpat <- 32
device <- rep(unlist(expand.grid(list(c("C", "Z"), c("C", "Z")))),
              anzpat / 4)
bleedtimes <- exp(rnorm(anzpat * 2, 0, .3) + as.numeric(device) * log(3))
pat <- as.factor(rep(1:anzpat, each=2))


survmod <- survreg(Surv(sapply(bleedtimes, min, 10), bleedtimes < 10) ~ device + frailty.gaussian(pat))


###  Fehler in residuals.survreg.penal(survmod) : 
###  Residualss not available for sparse models


###          (Intercept)                device frailty.gaussian(pat) 
###                    0                     0                     2 

Johannes Hüsing               There is something fascinating about science. 
                              One gets such wholesale returns of conjecture 
mailto:johannes at huesing.name  from such a trifling investment of fact.                
http://derwisch.wikidot.com         (Mark Twain, "Life on the Mississippi")

More information about the R-help mailing list