Hello,
I am confused about the order of nesting in mixed models using functions
like aov(), lme(), lmer().
I have the following data:
n subjects in either condition A or B
each subject tested at each of 3 numerical values ("distance" =
40,50,60), repeated 4 times for each of the 3 numerical values ("trial"
= 1,2,3,4)
Variable summary:
Condition: 2 level factor
Distance: numerical (but only 3 values) in the same units as "y"
Trial: 4 level factor
I expect the subjects' data to differ due to condition and distance, and
am doing repeated measurements to reduce any variability due to
measurement error.
Currently I'm using this model:
lme(y ~ Condition + Distance, random = ...)
the question is how do I organize the random statement? Is it:
random = ~1 | Subject
random = ~1 | Subject/Trial
random = ~1 | Trial/Subject
random = ~1 | Condition/Distance/Subject/Trial
...etc, or something else entirely?
Mostly I'm unclear about whether the Trials should be grouped under
subject because I expect the trials to be more similar within a subject
than across subjects, or whether subjects should be grouped under trials
because the trials are going to differ depending on the subject. If
trials should be grouped under subjects, then do the condition or
distance belong as well, since the trials will be most similar within
each distance within each subject?
Thanks in advance!
- Jon
--
Jon Zadra
Department of Psychology
University of Virginia
P.O. Box 400400
Charlottesville VA 22904
(434) 982-4744
email: za...@virginia.edu
<http://www.google.com/calendar/embed?src=jzadra%40gmail.com>
______________________________________________
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.
