[R] GAM for censored data? (survival analysis)

From: Eric Peterson <peterson_at_heritage.nv.gov>
Date: Fri, 29 Jun 2007 10:51:02 -0700


First let me admit that I am no statistician... rather, an ecologist with just enough statistical knowledge to be dangerous.  

I've got a dataset with percent ground cover values for species and other entities. The data are left censored at zero, in that percent ground cover cannot be negative. (My data rarely reach 100% cover so I haven't bothered with adding a right censoring at 100). I've done some previous analyses using survival analysis methods to create a predictive model for an entity of particular interest... library("survival"); survreg(Surv(Y) ~ X).  

However, I know my data do not really match linear modeling and would like to work with some alternate methods, one of which is GAM. I noticed that Yee and Mitchell (1991, p.589) stated that GAM is appropriate for "certain types of survival data". How do I implement a survival data model in GAM with R? I've searched both R help and the R site search, but not found anything relevant.  

Would it be as simple as library("survival"); library("mgcv"); gam(Surv(Y) ~ X) ???  

While I have your attention, I have a related second question. I'd like to model one entity (percent ground cover) as a function of another (also percent ground cover). Is there any way to deal with a censored predictor variable as well as the censored response?  

Citation: Yee, T. W. & N. D. Mitchell. 1991. Generalized additive models in plant ecology. Journal of Vegetation Science 2: 587-602.  

Thanks,
-Eric Peterson
Vegetation Ecologist
Nevada Natural Heritage Program

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