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st: Modeling control variables (covariates) in SEMs: What is the correct approach?
From
Johannes Kotte <[email protected]>
To
[email protected]
Subject
st: Modeling control variables (covariates) in SEMs: What is the correct approach?
Date
Fri, 18 Jan 2013 11:29:41 +0100
Hi everybody,
regarding the use of control variables (covariates) in SEMs I have
seen two different approaches and I am not sure which one is the
correct one. Can anybody help me?
Variables:
IV ...independent variable
MV ...moderator variable
DV ...dependent variable
CV1...control variable 1
CV2...control variable 2
*Approach 1*
(http://www.ats.ucla.edu/stat/stata/faq/sem_mediation.htm) is to use
the control variables in each of the equations:
sem (MV <- IV CV1 CV2) (DV <- MV IV CV1 CV2)
*Approach 2* (used by a fellow researcher I know) is to regress CV1
and CV2 on all other variables first and then do the rest of the
regressions without control variables:
sem (DV MV IV <- CV1 CV2) (MV <-IV) (DV<-MV)
To me, this approach looks incorrect. What I find particularly
confusing with this approach is that CV1 and CV2 are also being
regressed on IV.
I am grateful for feedback. Thanks in advance!
One more question comes to my mind: Some of my CVs are correlated at
the 5% level, but their correlation coefficients are below 0.3. Would
you exclude these CVs?
Thanks for your help!
Johannes
--
Johannes Kotte
Otto-von-Guericke-Universität | Fakultät Wirtschaftswissenschaften |
Lehrstuhl für Unternehmensführung und Organisation (Prof. Dr. Thomas
Spengler) | Postfach 4120, 39016 Magdeburg | www.ufo.ovgu.de
E-Mail: [email protected]
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