Hello everyone.  This is my first time subscribing to and posting to any R
mailing list, so I am unsure about protocols here.  Having said that, I have
been working with my research professor on fitting multi-level models using
school standardized test data.  We are looking to fit a model where student
scores over time are nested within students, which are nested within
teachers.  Additionally, we would like to include random effects on both the
intercept and on the slope associated with time (in this case, grade
level).  Unfortunately, the data is quite messy, and some students have just
one teacher in a school, while other students have several teachers in a
school.  The following model and analysis still seem run out of memory (or
at least cause R to crash to a generic Windows "R has a problem and needs to
close" window with no other error message on a fairly high-powered machine):

MathVAMForm1 <- as.formula("MATH_SCORE ~ GRADE +
                            (1 + GRADE | K20_ID:EMPLOYEE_ID) +
                            (1 + GRADE | EMPLOYEE_ID)")
MathVAMFit1 <- lmer(MathVAMForm1, Data)

In this code, K20_ID is a student ID, while the rest of the variables are
fairly self-explanatory.  We would also like to add a 4th level of nesting,
teachers within schools, but haven't tried to run that yet since the first
form did not work.

Just for the purposes of testing, we ran this model where observations were
nested within both students and teachers, students were cross-classified
with teachers but both were nested within schools, as shown below:

MathPalForm2 <- as.formula("MATH_SCORE ~ GRADE +
                            (1 + GRADE | K20_ID:INSTITUTION_ID) +
                            (1 + GRADE | EMPLOYEE_ID:INSTITUTION_ID) +
                            (1 + GRADE | INSTITUTION_ID)")
MathPalFit2 <- lmer(MathPalForm2, Data)

This model fit quickly and (as best we can tell) correctly, although it is
not really the theoretical model we would like to fit.

Additionally, for testing, we ran a model that just had observations nested
within teachers, which were nested within schools, as shown below:

MathNoStForm3 <- as.formula("MATH_SCORE ~ GRADE +
                            (1 + GRADE | EMPLOYEE_ID:INSTITUTION_ID) +
                            (1 + GRADE | INSTITUTION_ID)")
MathNoStFit3 <- lmer(MathNoStForm3, Data)

This model also fits quickly and correctly, and is definitely not the
theoretical model we would like to fit.


Are there any suggestions on what syntax or setup we might be doing wrong to
fit our desired model (Form 1 above)?  Additionally, are there any
characteristics of the data that may be causing trouble with fitting Form 1
that would not cause trouble with Forms 2 or 3?  We have been scratching our
heads with this for a bit now, and any feedback would be welcome.  Thanks,
and have a great day!

-Robert Sandbach
(rojosa@gmail.com)
Graduate Student
University of Florida
College of Education
Research & Evaluation Methodology

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