Multilevel mediation with two mediators PreviousNext
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 Nick Brisbon posted on Friday, March 18, 2016 - 12:00 pm
I've run a model (1-1-1) with a single mediator and would like to extend this for a second mediator in serial. I've basically extended Model H (http://www.statmodel.com/download/Preacher.pdf) from Preacher's website. Is this appropriate? I just defined an additional pathway and indirect effect.

To be clear, this is using diary data over 7 days. So that there are 7 timepoints for each variable nested within individuals. The variables on level 2 are preceded with a "PM" and are the "person-mean". The variables on level 1 are preceded by a "WP" and are "person-mean centered".


ANALYSIS: TYPE IS TWOLEVEL;

MODEL:
%WITHIN%
y WP_x WP_m1 WP_m2;
WP_m1 ON WP_x (aw);
WP_m2 ON WP_m1 (bw);
y ON WP_m2 (cw);
y ON WP_x;
[x@0]
[m1@0]
[m2@0]
%BETWEEN%
y PM_x PM_m1 PM_m2;
PM_m1 ON PM_x (ab);
PM_m2 ON PM_m1 (bb);
y ON PM_m2 (cb);
y ON PM_x;
[y PM_x PM_m1 PM_m2];
MODEL CONSTRAINT:
NEW(indb indw);
indb=ab*bb*cb;;
indw=aw*bw*cw;
 Kristopher J. Preacher posted on Tuesday, March 22, 2016 - 12:38 pm
There is nothing wrong with the syntax, but I might suggest regressing WP_M2 on WP_x and regressing y on WP_m1 (and corresponding regressions in the %BETWEEN% model). It is typical to include all these regressions in serial mediation models. Also, if your data are from a daily diary study you might have autocorrelated residuals within person, which this model does not accommodate.
 Nick posted on Wednesday, March 23, 2016 - 12:42 pm
Thank you very much for the help!

The data are from a daily diary study. What would you suggest? Is there a more appropriate model that would take auto-correlated residuals into consideration? Could I use the current model and simply use lagged variables for M1, M2, and Y as covariates? I've seen this done in similar situations. Any advice or suggestions are greatly appreciated. Thank you in advance!
 Kristopher J. Preacher posted on Wednesday, March 23, 2016 - 8:33 pm
That might work for the 'within' model, assuming equally spaced occasions and a constant degree of autocorrelation. An alternative is to run the whole thing as a single-level model using wide format multivariate data, avoiding MSEM altogether. This is the same trick that justifies running latent growth curve models as single-level SEM.
 Sascha Aha posted on Thursday, April 05, 2018 - 6:46 am
I'm also planning to run a serial multilevel mediation model with diary data from a 14 day sampling period (focus on within-person effects (level-1)). I think that the above mentioned syntax could work for me as well, but now I'm wondering how to enter covariates into the model?

Best, Sascha
 Bengt O. Muthen posted on Thursday, April 05, 2018 - 2:37 pm
Just add them in the ON statements.

You might also want to take a look at our web page

http://www.statmodel.com/TimeSeries.shtml
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