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st: Modeling control variables (covariates) in SEMs: What is the correct approach?


From   Johannes Kotte <johannes.kotte@st.ovgu.de>
To   statalist@hsphsun2.harvard.edu
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: johannes.kotte@st.ovgu.de


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