Cheers guys that's helpful. Doug, you're right, my code for ff should have
been
for (i in 1:length(y))
{if (f1[i]==after f3[i]==1) ff[i]-1, after
else if(f1[i]==after f3[i]==2) ff[i]-2, after
else if(f1[i]==before f3[i]==1) ff[i]-1, before
else if(f1[i]==before f3[i]==2) ff[i]-2, before}
On Thu, Oct 8, 2009 at 1:57 AM, Paul Chatfield p.s.chatfi...@rdg.ac.uk wrote:
Cheers guys that's helpful. Doug, you're right, my code for ff should have
been
for (i in 1:length(y))
{if (f1[i]==after f3[i]==1) ff[i]-1, after
else if(f1[i]==after f3[i]==2) ff[i]-2, after
else
That's solved it. Superb!
All you probably need is to make f2 a factor (e.g., y ~ factor(f2) |
f1). Otherwise dotplot() doesn't know which one to treat as
categorical.
-Deepayan
--
View this message in context:
## Paul
## I think you are looking for interaction2wt
y - rnorm(36)
f1 - rep(c(after, before), 18)
f2 - rep(1:3, 12)
f3 - rep(1:2, each=18)
## your definition of ff was faulty. It gave a constant.
f3.f1 - interaction(f3, f1)
interaction.plot(f3.f1, f2, y)
f2 - factor(f2)
f3 - factor(f3)
##
I'm not sure if this is exactly what you are looking for but I would
generally create an interaction plot using the lattice 'dotplot' with
type = c(p,a) so I get both the original data and the lines
joining the averages for the different factor levels. I also prefer
the horizontal orientation to
5 matches
Mail list logo
