And if you make 'year' a factor with levels '2007' and '2008'
you'll get your second wish.

Peter

Sundar Dorai-Raj wrote:
I think this ought to work for you:

library(lattice)
set.seed(42)
d <- data.frame(year  = c(rep(2007,12), rep(2008,12)),
                treatment = rep(LETTERS[1:3], each = 4, times = 2))
d$cover <- rnorm(nrow(d))
d$variable <- rnorm(nrow(d))

xyplot(variable ~ cover | year, d,
       panel = function(x, y, ...) {
         panel.superpose(x, y, ...)
         panel.lmline(x, y, ...)
       },
       groups = treatment)

HTH,

--sundar

On Fri, Sep 18, 2009 at 3:42 PM, Seth W Bigelow <sbige...@fs.fed.us> wrote:
I wish to identify groups representing different treatments, but to plot
them and do a regression using a continuous variable ("cover")
ignoring the groupings.

d$year <- NA
d$year <-c(rep(2007,12), rep(2008,12))
d$treatment <- c(rep("A",4),rep("B",4),rep("C",4), rep("A",4), rep("B",4),
rep("C",4))
d$cover <- rnorm(24)
d$variable <- rnorm(24)

xyplot(variable ~ cover | year, d,
       type=c("p","r"),
       groups=treatment
       )

As it stands, a different regression line is plotted for each treatment.
Oh, and how do I display the actual numeric value of year (e.g., "2007")
in the strip, rather than the word "year"?

--Seth



Dr. Seth  W. Bigelow
Biologist, USDA-FS Pacific Southwest Research Station
1731 Research Park Drive, Davis California
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