Hi all -

 

I am unsophisticated user in need of some help.  I have a study in which I
have two random factors: subject and item.  I also have 3 fixed effects: 1.
X1 (continuous values), 2. Y (continuous values), and 3. Age (has two levels
"young" and "old").  My dependent variable is Z.

 

I am using the following formula to predict the effect of each factor:

fit1 <- lmer(Z ~Age * X1 * Y + (1 | Subject) + (1 | Stim), method = "ML",
data = d)

 

furthermore, I have the option of using a different model (theoretical, not
statistical) in order to calculate values for X.  I will call this X2.  This
means that I could also get a fit in the following way:

fit2 <- lmer(Z ~Age * X2 * Y + (1 | Subject) + (1 | Stim), method = "ML",
data = d)

 

 

Here is the question:

Is there anyway to compare fit1 and fit2?  would anova (fit1, fit2) be
appropriate in this case?  (if possible, would you be kind enough to give me
references on the answer?)

 

Any help is greatly appreciated.

-shabnam


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