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Re: Re: Re: st: RE: SEM with bootstrapping for analysis of mediation

 From Philip Ender To statalist@hsphsun2.harvard.edu Subject Re: Re: Re: st: RE: SEM with bootstrapping for analysis of mediation Date Wed, 11 Jul 2012 22:34:36 -0700

```Oops, my posting with subject "st: Re: question about graphs" should have been
"Re: Re: Re: st: RE: SEM with bootstrapping for analysis of mediation".   I am
reposting with the correct Subject lis

"Iyer, Neeraj N" <niyer@purdue.edu> wrote:

Thank you. I did not want to assume that the direct and indirect
effects would be adjusted for the covariates;

However, in the command line  sem (MV <- IV CV1 CV2 CV3 CV4 ) (DV <-
MV IV CV1 CV2 CV3 CV4),
I was unable to fathom how STATA would know which one of
IV/CV1/CV2/CV3/CV4 is the true Indep. Var.
In other words, since " IV CV1 CV2 CV3 CV4" are common to both paths
how can STATA differentiate between
the variables, which will answer the question, "Whose indirect effect
are we observing"?

Hence, I was looking for bootstrap CI for the indirect effect of each
individual variable, or a partitioned
bootstrap CI. Is this partitioning plausible?
------

Dear Neeraj,

Okay, now I can see what you're asking and I also see that the
-indireff.ado- program needs to be modified due to the four
covariates.
The program get a vector of direct, indirect, and total effects for
each bootstrapped sample, so the number of covariates affects
the position of the coefficient of interest.  With four covariates you
will need to change the 3 to 7 in following lines

return scalar indir  = el(bi,1,7)
return scalar direct = el(bd,1,7)
return scalar total  = el(bt,1,7)

These coefficients will give you the indirect, direct and total effect
for the IV on the DV.

The easiest way to figure this out is to rum the -sem- and -estat
effects- the normal way without bootstrapping and look at
the vectors r(indirect), r(direct) and r(total)

I hope may explanation is clear.

--
Phil Ender
UCLA Statistical Consulting Group
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