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I have a 111 mediation (see below an MSEM code). My problem is that I have a level 2 moderator as well. As far as I could understand, level 2 measures can influence level 2 constructs (between), but not level 1 (within). Am I right so far? If so can someone help with the implementation of that into the code below? TITLE: 111 mediation (MSEM) DATA: FILE IS mydata.dat; VARIABLE: NAMES ARE id x m y; USEVARIABLES ARE id x m y; CLUSTER IS id; ANALYSIS: TYPE IS TWOLEVEL RANDOM; MODEL: %WITHIN% m ON x(aw); ! regress m on x, call the slope "aw" y ON m(bw); ! regress y on m, call the slope "bw" y ON x; ! regress y on x %BETWEEN% x m y; ! estimate Level2 (residual) variances for x, m, and y m ON x(ab); ! regress m on x, call the slope "ab" y ON m(bb); ! regress y on m, call the slope "bb" y ON x; ! regress y on x MODEL CONSTRAINT: ! section for computing indirect effects NEW(indb indw); ! name the indirect effects indw=aw*bw; ! compute the Within indirect effect indb=ab*bb; ! compute the Between indirect effect OUTPUT: TECH1 TECH8 CINTERVAL; ! request parameter specifications, starting values, ! optimation history, and confidence intervals for all effects Sincerely, 


I am not into the numbering approach of characterizing twolevel mediation modeling, but looking at Bauer et al (2006) in Psych Methods Figure 2, bottom, it looks to me that 111 mediation has a mediation model on the Within level and unrestricted random effects on the Between level. You pose a model for the random effects on Between. It happens to be a saturated model so it becomes the same as unrestricted. Then you say "level 2 measures can influence level 2 constructs (between), but not level 1 (within)." Let's scrutinize the second part of that statement. It sounds like you want "221" as in top of Figure 2. Using an education example, you have a teacher background variable influencing a teacher dependent variable (22) which you want to influence a student dependent variable (221). This is done by letting the teacher dependent variable influence the betweenlevel part of the student variable on Between, that is the random intercept (varying over teachers/classrooms) of the student variable. The model you have written in your Mplus input does this with both M and Y having betweenlevel random intercepts. I don't see any moderator in your Mplus input. A moderator is an interaction. 


You may also want to take a look at the Topic 7 handout on our web site. Slides 4445 talk about random intercepts and random slopes (crosslevel interaction). 

Sean Lane posted on Wednesday, August 24, 2011  9:47 am



I'm trying to fit a model similar to that listed above (using the Bauer et al syntax), but I get an error message saying that Monte Carlo integration is needed. When I specify Monte Carlo integration I get another error message saying that withinperson variables cannot be on the right hand side of an ON statement. However, since I didn't specify any variables as BETWEEN I should be able to use them as WITHIN or BETWEEN, right? VARIABLE: NAMES ARE myid pol anger attackm; MISSING ARE ALL (99); USEVARIABLES ARE myid pol anger attackm; CLUSTER IS myid; ANALYSIS: TYPE IS TWOLEVEL RANDOM; !ALGORITHM = INTEGRATION; !INTEGRATION = MONTECARLO; MODEL: %WITHIN% sa  anger ON pol; sb  attackm ON anger; sc  attackm ON pol; %BETWEEN% sa sb sc pol anger attackm; sa WITH sc pol anger attackm; sa WITH sb(cab); sb WITH sc pol anger attackm; sc WITH pol anger attackm; anger ON pol(ab); attackm ON anger(bb); attackm ON pol; [sa](aw); [sb](bw); MODEL CONSTRAINT: NEW(a b indb indw); a=aw+ab; ! compute Between a path b=bw+bb; ! compute Between b path indw=aw*bw+cab; ! compute the Within indirect effect indb=a*b; ! compute the Between indirect effect OUTPUT: TECH1 TECH8 CINTERVAL; Any help is greatly appreciated. Thanks! 


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