Thanks for providing a reproducible example.

Using the plyr package you can write your whole computation more compactly:

library(plyr)
library(caTools) #for trapz

auc <- ddply(lab.samples, .(challenge, subid),
             function(df) {
  df$time <- c(0, seq(60,by=10, len=nrow(df)-1))
  summarize(df,
            cortisol = trapz(time, cortisol),
            amylase = trapz(time, amylase))
})

On Mon, Mar 19, 2012 at 2:44 PM, David Perlman <dperl...@wisc.edu> wrote:

> I could do this in various hacky ways, but what's the right way?
>
> I have a nice application of the by function, which does what I want.  The
> output looks like this:
>
> > auc_stress
> lab.samples.stress$subid: 2
>  cortisol amylase
> 1   919.05  6834.8
>
> ---------------------------------------------------------------------------------------------------------------------------
> lab.samples.stress$subid: 3
>   cortisol  amylase
> 11   728.25 24422.05
>
> etc.
>
> What I want is a data frame roughly like this:
>
> subid  cortisol.auc  amylase.auc
> 2      919.05        6834.8
> 3      728.25        24422.05
>
> etc.
>
> What is a nice way to make that happen?
>
>
>
> Here is the code and data that I am using, which should run directly if
> you copy and paste it:
>
>
> sanity.check<-read.csv("
> http://brainimaging.waisman.wisc.edu/~perlman/testdata.csv";, header=TRUE,
> sep = ",")
> lab.samples <- subset(sanity.check,Sample!='before bed' & Sample!='morning
> after')
> lab.samples$Sample<-factor(lab.samples$Sample)
> lab.samples.stress<-subset(lab.samples,challenge=='stress')
> lab.samples.control<-subset(lab.samples,challenge=='control')
>
> auc_ground <- function(sub_df) {
>        print(sub_df)
>        auc<-sub_df[1,]*0
>        timedif<-c(60,10,10,10,10,10,10)
>        for (i in 1:(nrow(sub_df)-1) ) {
>                print(c(i,i+1))
>                #print(c(values[i],values[i+1]))
>                pair_area<-(sub_df[i,]+sub_df[i+1,])*timedif[i]/2
>                auc<-auc+pair_area
>        }
>        auc
> }
>
> auc_stress<-by(lab.samples.stress[c('cortisol','amylase')],
> lab.samples.stress$subid, auc_ground, simplify=T)
> auc_control<-by(lab.samples.control[c('cortisol','amylase')],
> lab.samples.control$subid, auc_ground, simplify=T)
>
>
> Thanks for your help!
>
> P.S. sorry if this question has been answered before, it is nearly
> impossible to get useful google results on search terms like "by"...  too
> common word...
>
>
> -dave----------------------------------------------------------------------
> A neuroscientist is at the video arcade, when someone makes him a $1000 bet
> on Pac-Man. He smiles, gets out his screwdriver and takes apart the Pac-Man
> game. Everyone says "What are you doing?" The neuroscientist says "Well,
> since we all know that Pac-Man is based on electric signals traveling
> through these circuits, obviously I can understand it better than the other
> guy by going straight to the source!"
>
> ______________________________________________
> 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.
>

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