[R-lang] comparing two mixed-effects models

[shabnam shademan]

3. could I use the same formula to examine only one "Age" group (removing
"Age" as a factor in the formula, of course), even if I am going to later
proceed and re-examine the data for a larger young/old set?


I am not sure that I understand what you mean. Nothing prevents you from
exploring e.g. only data from "young" people, but be aware that whatever
conclusions you draw out of the examination of that subset of your data, may
not generalize to the entire sample (and hence not to the population
represented by the entire sample).

SS: the data shows an effect of "Age" (which has two levels "young" and
"old"). I wanted to test a subset of the data that included only "young" and
see whether there is an interaction between X and Y, for them as a subset.
I was thinking that the result may be generalized to only "young"
population, and not the entire sample.  Just want to make sure that I am not
doing something that has problems that I am not aware of.  I hope I was able
to state the question more clearly.


yes, this is ok.  be aware, however, that by splitting the data set you
loose power. so failure to detect the X*Y interaction MAY be due to lack of
power. an additional test you could confirm is a three-way interaction for
the entire data set X*Y*Age. If it is NON-significant that is a further
indication that the X*Y interaction holds for both age groups. 

SS: Thanks.  The X*Y interaction does not disappear for the smaller set, and
the three-way interaction Age*X*Y in not significant.  So, it looks like all
is well.

 

 

finally, I always advise visualization of the data set (as a way to compare
the effects of X*Y for young vs. old people).

SS:I am not sure what kind of visualization you are recommending for X*Y.

 



is this useful? I am cc-ing the language list, so that other people can
correct me.

Yes, it is.  Thanks for taking the time.

-shabnam

 



Florian

 

Thanks very much.

-shabnam

 




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