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 _______________________________________________ R-lang mailing list [email protected] https://ling.ucsd.edu/mailman/listinfo.cgi/r-lang
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