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st: RE: How do I graph prediction of mean growth trajectory?
From
"Martin Weiss" <[email protected]>
To
<[email protected]>
Subject
st: RE: How do I graph prediction of mean growth trajectory?
Date
Fri, 21 May 2010 23:32:53 +0200
<>
" A related question is this: If I have to produce these lines
separately, creating six graphs, is there a way I can overlay them?
"
Overlaying these days is accomplished via -twoway- calls:
***********
sysuse auto, clear
tw (line price number) (line weight number)
***********
This could be telescoped to
-tw (line price weight number)-
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of David Torres
Sent: Freitag, 21. Mai 2010 23:27
To: [email protected]
Subject: st: How do I graph prediction of mean growth trajectory?
Hello all,
I am trying to graph expected growth in IQ scores by maternal IQ class
and treatment/control group assignment. Since there are three
maternal IQ classes and two group assignments, I should have six lines
or growth curves.
Now, my models were calculated using Stata's -xtmixed- command, so
I've been following Rabe-Hesketh and Skrondal's text on multilevel
modeling, 2nd edition, page 210-220. They give an example of how to
graph growth, but the example does not include interactions nor does
it allow for the slopes to change between some other time-varying
covariate, which I have in my model. The outcome is test score, of
course. The list of the predictor variables in the full model from
which I would like to create my graphs follow:
1. age
2. age^2
3. assessment given (two different assessments over several years, so
this is entered as a time-varying covariate. It would be great if I
could get the slope to vary by assessment) - Stanford-Binet or Wechsler
4. home environment - 0/1, less stimulating/more stimulating
5. treatment - 0/1, control/treatment
6 & 7. maternal IQ class - 1/2/3, IQ<=75/IQ between 76&90/IQ between 91&110
1 is the reference category
8 & 9. interaction between treatment and maternal IQ class
All of the variables in this model are significant, so I want to make
sure that my graph accurately reflects that. Also, I understand that
since interactions can be difficult to interpret sometimes a visual
represention of the data are always good as an accompaniment.
A related question is this: If I have to produce these lines
separately, creating six graphs, is there a way I can overlay them?
--------------------------------------------
David Diego Torres, MA(Sociology)
PhD Candidate in Sociology
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