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" I am a bit confused about the number of levels in a multilevel model. In
Stata v 10 manual XT page 293 (xtmixed). In example 4 they describe a "2
level model" with individuals, states and regions. To me it looks like a 3
level model. What´s going on?"
The 10 manual says quite clearly on page 286 (quote is from the 11 manual):
" Finally, using formulation (2) and its multilevel extensions requires one
important convention of terminology. Model (2) is what we call a one-level
model, with extensions to two, three, or any
number of levels. In our hypothetical two-level model with classes nested
within schools, the schools
are considered the first level and classes, the second level of the model.
This is consistent with
terminology used elsewhere, e.g., Pinheiro and Bates (2000), but differs
from that of the literature
on hierarchical models, e.g., Skrondal and Rabe-Hesketh (2004). In that
literature, our schools and
classes model would be considered a three-level model, with the students
forming the first level,
classes the second, and schools the third. Not only is there one more level
(students) but the order
is reversed."
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Tomas Lind
Gesendet: Sonntag, 20. Dezember 2009 17:28
An: [email protected]
Betreff: st: xtmixed and multilevel models
Dear listers,
I am a bit confused about the number of levels in a multilevel model. In
Stata v 10 manual XT page 293 (xtmixed). In example 4 they describe a "2
level model" with individuals, states and regions. To me it looks like a 3
level model. What´s going on?
I can´t find any example in xtmixed-regression with explanatory variables on
a group level (for example on level 2 in a 2-level model). If I want to
explain why a random intercept varies between group 2 units because of
differences in socioeconomic status between groups do I proceed like this?
I generate a new variable to the dataset "group_mean_ses" which is the mean
ses within group. All individuals in a group have the same value.
Now I add the variable group_mean_ses as an explanatory variable in the
xtmixed model (don´t worry over the variables, this is not a real study).
xtmixed health age sex ses group_mean_ses || group
If I have a random slope on some individual level variable, say age, and
want to explain that with group_mean_ses should I generate a cross-level
interaction variable.
generate gmsXage = group_mean_ses * age
and then specify the model as
xtmixed health age sex ses group_mean_ses gmsXage || group : age
All comments or ideas are welcome.
/Tomas
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