On Mon, Aug 23, 2010 at 3:58 PM, Lei Liu liu...@virginia.edu wrote:
Hi there,
I want to make trajectory plots for data as follows:
ID time y
1 1 1.4
1 2 2.0
1 3 2.5
2 1.5 2.3
2 4 4.5
2 5.5 1.6
2 6
On Mon, Aug 23, 2010 at 4:16 PM, Gabor Grothendieck
ggrothendi...@gmail.com wrote:
On Mon, Aug 23, 2010 at 3:58 PM, Lei Liu liu...@virginia.edu wrote:
Hi there,
I want to make trajectory plots for data as follows:
ID time y
1 1 1.4
1 2 2.0
1 3
and some more options...
dat - structure(list(ID = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L),
.Label = c(1, 2), class = factor),
time = c(1, 2, 3, 1.5, 4, 5.5, 6),
y = c(1.4, 2, 2.5, 2.3, 4.5, 1.6, 2)),
.Names = c(ID, time, y),
row.names = c(NA, -7L), class = data.frame)
library(lattice)
On Mon, 2010-08-23 at 15:58 -0400, Lei Liu wrote:
That is, I will plot a growth curve for each subject ID, with y in
the y axis, and time in the x axis. I would like to have all growth
curves in the same plot. Is there a simple way in R to do it? Thanks a
lot!
This article, entitled,
Hi Lei,
Hope you don't mind I'm moving this back to the list in case others
may benefit. Answers below...
On Mon, Aug 23, 2010 at 3:37 PM, Lei Liu liu...@virginia.edu wrote:
Hi Kingsford,
Thanks a lot! I got some help from my colleague by using the following code:
xyplot(y~month,group=id,
Hi:
On Mon, Aug 23, 2010 at 4:19 PM, Kingsford Jones
kingsfordjo...@gmail.comwrote:
Hi Lei,
Hope you don't mind I'm moving this back to the list in case others
may benefit. Answers below...
On Mon, Aug 23, 2010 at 3:37 PM, Lei Liu liu...@virginia.edu wrote:
Hi Kingsford,
Thanks a
On Mon, Aug 23, 2010 at 6:19 PM, Dennis Murphy djmu...@gmail.com wrote:
This is an excellent idea - the only snag might occur if someone wants
the mean line to be thicker :)
fortunately, with your lattice solution this is easily accomplished by
passing a vector to lwd:
i - c(1, 1, 1, 3)
Hi:
I think it would be tough to do that in qplot(), but it's easier in
ggplot(), even if you don't add the mean information to the data frame.
Here's one way - use the three person data frame (call it dat1) and the
mean.y data frame that you created from aggregate() without adding the
factor
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