[R-lang] comparing two mixed-effects models

[shabnam shademan]

Hi all -

 

I am unsophisticated user in need of some help.  I have a study in which I
have two random factors: subject and stimuli item.  I also have 3 fixed
effects: 

1. y=similarity-based score (continuous values)

2. Age (has two levels "young" and "old")

3. x=grammatical-based score (continuous values).  

My dependent variable is z=item ratings from subjects.

 

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

 

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

 

furthermore, I have the option of using a different grammatical model 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 | Stimulus), method =
"ML", data = d)

 

 

Here are the questions:

1. Is there anyway to compare fit1 and fit2?  

2. would anova (fit1, fit2) be appropriate in this case?  (if possible,
would you be kind enough to give me references on the answer?)

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?

 

Any help is greatly appreciated.

-shabnam

 

 

 

-------------- next part --------------
An HTML attachment was scrubbed...
URL: https://ling.ucsd.edu/pipermail/r-lang/attachments/20070508/ccdc8ab0/attachment-0001.htm