On Dec 13, 2008, at 11:37 AM, Jason Augustyn wrote:
Hi David, thanks for the quick response. I did look at the help
files for model.tables and se.contrast and neither seemed
appropriate. I probably wasn't clear enough in my original email, so
here's more information:
I'm analyzing data from a psychology experiment on how people
allocate visual attention when walking over difficult terrain. In
the experiment subjects walked on a treadmill for 30 minutes while
performing an attention-demanding reaction time task. In one
condition they could walk freely, whereas in another condition they
had to avoid markings placed on the treadmill belt to simulate
obstacles. The stimuli for the reaction time task were placed either
at eye-level or near the ground.
The dependent measure I'm working with comes from an eye-tracking
system that we ran while subjects walked, which provided data on the
amount of time subjects looked at the reaction time stimuli versus
the treadmill belt. We divided the fixation time data sets for each
subject into three time bins to look at changes in fixation behavior
over time.
So the full design of the study is a 2x2x2x3 with repeated measures
on all factors. The factors were:
Markings (Levels: present, absent)
Reaction time task "Position" (Levels: eye-level, ground-level)
Eye fixation "Plane": (Levels: RT stimuli, treadmill belt)
Time bin (Levels: 1,2,3)
A call to aov yields main effects of Markings, Position, and Plane,
as well as a Markings*Plane interaction. For comparison purposes I
ran the same analysis in SPSS and got equivalent ANOVA results, so
I'm confident the model has been set up properly in R.
Now, what I want to get are means and standard errors for the main
effects and interaction to generate figures for publication using
other software. As stated in my initial post, I got the means using
model.tables and they are correct as compared with the SPSS output.
However, I cannot get the standard errors for the means. I've tried
various things in R and cannot get values that correspond to the
SPSS output.
My understanding is that the se's are for the effects, i.e. on
parameter estimates for differences, rather than for the means
themselves. One get these (at least in the example on the help page)
with:
model.tables(npk.aov, "means", se = TRUE)
Does not this give you what you need?
model.tables(rawfixtimedata.aov,"means", se=TRUE)
I am not sure what you are referring to when you ask for se's for the
"means" in the presence of interactions. How are you going to
partition the cases? Would one case contribute to both the main "mean"
and to any or all the interaction "means" in which it might be involved?
--
David Winsemius
Again, I assume there is an R function that can get me the values I
need and would hugely appreciate any pointers. In case you're
wondering why I'm bothering with running the analyses in R given
that I already have them done in SPSS, I'm just generally interested
in learning to use R to have an additional analysis tool in my
toolkit.
Thanks for any help!
Cheers,
Jason
On Sat, Dec 13, 2008 at 9:04 AM, David Winsemius <dwinsem...@comcast.net
> wrote:
On Dec 12, 2008, at 10:59 PM, js.augus...@gmail.com wrote:
Hi all,
I'm quite new to R and have a very basic question regarding how one
gets
the standard error of the mean for factor levels under aov. I was
able to
get the factor level means using:
summary(print(model.tables(rawfixtimedata.aov,"means"),digits=3)),
where rawfixtimedata.aov is my aov model. It doesn't appear that
there is
an equivalent function to get the standard errors for the factor
levels.
I searched through the help archives and documentation but could not
find
anything that would help resolve my problem. I'm sure there is a
trivial
solution, but I would sincerely appreciate having someone more expert
dispel my ignorance.
Have you looked at the help page for model.tables? ... and perhaps ?
se.contrast
There are arguments to that function that result in standard errors
for _effects_. If standard errors on the contrasts are not what you
wanted, then perhaps a full example would help.
--
David Winsemius
Cheers,
Jason Augustyn
[[alternative HTML version deleted]]
______________________________________________
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.
______________________________________________
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.
