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I am struggling with my moderation model. All my variables are at the withinlevel and continuous. I would like to test if women's shame (ShameW) moderates the associations between women's empathy (EmpW) and partners' empathy (EmpP) on women's pain (Pain) and both partners' distress (DetW and DetP) : USEVARIABLES = EmpW EmpP Pain DetW DetP ShameW IntW IntP; CLUSTER = Couple ; WITHIN EmpW EmpW ShameW IntW IntP Pain DetW DetP ; DEFINE: IntW=EmpW*ShameW ; IntP=EmpP*ShameW ; CENTER EmpW EmpP ShameW Pain DetP DetP (GROUPMEAN); ANALYSIS: TYPE = twolevel random ; MODEL: %BETWEEN% %WITHIN% Pain ON EmpW ShameW EmpP IntW IntP; DetW ON EmpW ShameW EmpP IntW IntP; DetP ON EmpP ShameW EmpA IntW IntP; Pain WITH DetW DetP ; DetP WITH DetW ; EmpW WITH EmpP ; MODEL CONSTRAINT: NEW (LOW_M MED_M HIGH_M); LOW_M = 0.85; !  SD MED_M = 3.37; ! mean value HIGH_M = 5.89; ! + SD I am stuck here. I probably have to calculate simple slopes for each value of the moderator and use loop plot to plot model for low, med, high values of the moderator, but I don't know how to write the syntax so I could have the interaction effects. If this syntax is not the best, do you have another one? 


You can use syntax in line with the RMA book examples for chapter 1 at http://www.statmodel.com/mplusbook/chapter1.shtml See the script for: Table 1.8, Part 2, p. 31: Regression with a randomized intervention using treatmentbaseline interaction and LOOP PLOT of moderation 


See also the first example of the Topic 11 Short Course video and handout on our website at http://www.statmodel.com/course_materials.shtml 


Thank you very much for such a quick response! I looked at the script in Table 1.8, part 2, p. 31. I fear that what I am struggling with is the formula, which directly translate into my syntax. I understand with a dyad dataset (no moderator), we would have two equations in SEM: Y1 = b0 + b1X1 + b2X1 + e1 Y2 = b0 + b2X1 + b1X1 + e2 and with a moderator we would have (correct me if I am wrong) : Y1 = b0 + b1X1 + b2X2 + b3M + b4X1M + b5X2M + e1 Y2 = b6 + b7X2 + b8X1 + b9M + b10X2M + b11X1M + e2 In your example you wrote : model constraint: LOOP(x,1,1,0.1); PLOT(effect); effect = b1 + b3*x; However, could you help me with the 'effect formula' part? Should I have two lines here (dyad dataset)? Lastly, you set 0.1 increment in your example. Is it the usual choice? 


Your 2 moderator equations look correct. The moderator functions are: Y1: (b1+b4*M) for X1 and (b2+b5*M) for X2 Y2: (b8+b11*M) for X1 and (b7+b10*M) for X2. 


Does this looks correct? I created equations for both y1 and y2 DVs. Only y1 are shown due to size limit. MODEL CONSTRAINT: NEW (LOW_M MED_M HIGH_M); NEW (SIMP_LOy1 SIMP_MEDy1 SIMP_HIy1 SIMP_LOy2 SIMP_MEDy2 SIMP_HIy2); LOW_M = 0.85; MED_M = 3.37; HIGH_M = 5.89; SIMP_LOy1 = (b1 + b4*LOW_M)+(b2 + b5*LOW_M); SIMP_MEDy1 = (b1 + b4*MED_M)+(b2 + b5*MED_M); SIMP_HIy1 = (b1 + b4*HIGH_M)+(b2 + b5*HIGH_M); ! Same but with y2 equations. PLOT(LOMODy1 MEDMODy1 HIMODy1 LOMODy2 MEDMODy2 HIMODy2); LOOP(ShameW,1,5,0.1); LOMODy1 = (b0 + b3*LOW_M) + ((b1 + b4*LOW_M)+(b2 + b5*LOW_M))*ShameW; MEDMODy1 = (b0 + b3*MED_M) + ((b1 + b4*MED_M)+(b2 + b5*MED_M))*ShameW; HIMODy1 = (b0 + b3*HIGH_M) + ((b1 + b4*HIGH_M)+(b2 + b5*HIGH_M))*ShameW; !Same but with y2 equations. 


No, you should not add the 2 terms (b1 + b4*LOW_M)+(b2 + b5*LOW_M); they represent different things  the first part is the X1 effect and the second part is the X2 effect. You can look at each separately. I think you should consult with a statistician  someone who is familiar with moderation modeling. We can not teach it here. 

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