Hi Rich, So what you're faced with is that the cenros() function has no built-in methods for grouping or subsetting -- unlike some other R methods, especially those that work with the lattice package, or the many modeling functions like lm() that have a subset argument or employ a conditioning syntax for models [like y ~ x | g ]. In effect, this means you have to roll your own.
The wide format could help, but you would still probably end up writing loops. Each parameter would then presumably be represented by two columns, one for the result, one for non-detection indicator. And they would all have different names, such as ceneq1.ag, ceneq1.al, and so on. I think you'd probably end up with more complicated scripts. This approach is especially tricky if not all analtyes and locations were sampled on the same days (which is normally the case for my data). You're probably aware that there are various functions for splitting a dataframe into subsets and then applying the same function to every subset, such as by() and aggregate(), and probably others. These may turn out to be fairly simple to use with a NADA function such as cenros(), but you won't really know until you start trying them. One can also do it oneself with constructs like tmpsub <- split( mydf, list(mydf$site, mydf$param) ) tmpss <- lapply(tmpsub, myfun) where myfun is a wrapper function around, say, cenros(). This is obviously just an outline. -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000 East Ave., L-627 Livermore, CA 94550 925-423-1062 On 7/5/12 1:15 PM, "Rich Shepard" <rshep...@appl-ecosys.com> wrote: >On Thu, 5 Jul 2012, MacQueen, Don wrote: > >> This example follows exactly the example in ?cenros. > >> with( subset(yourdataframe, param=='Ag'), cenros(quant,ceneq1) ) > >> This should do a simple censored summary statistica calculation for >>silver >> (assuming quant contains your reporting level for censored results, >>which >> appears to be the case). > >Don, > > That makes sense to me. I was hoping to avoid subsetting the data frame >for each of the 37 chemical parameters, but ... I will review the use of >with(). > >> I'd also suggest you try to load your data so that site and param are >>not >> factors, though this could depend on your ultimate analysis. > > I do need to differentiate results by site and chemical paramater. > >Many thanks, > >Rich > >______________________________________________ >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. ______________________________________________ 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.
