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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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