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
> [[alternative HTML version deleted]]
>
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>
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