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I have multilevel data (two nested levels: individual and team) and an upper level and lower level mediation. I will hypothesize that an individual-level predictor (X) affects a group level mediator (M1), and affects another individual level mediator (M2), which, in turn affects a group level outcome (Y). Is there a way to test this model? X (individual) - M1 (group level) - M2 (individual) - Y (group level) |
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You would specify the model you show as follows where x and m2 are not put on the WITHIN list and m1 and y are put on the BETWEEN list: %WITHIN% %BETWEEN% m1 ON x; m2 ON m1; y ON m2; |
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Hello, I find this forum extremely helpful and have already learned a lot. But now I have a problem where I can't find a solution: I am having a multilevel 2-1-1 mediation with 2 predictors (x1, x2) and a dichotomous mediator (m) and a number of control variables (cv). The model works very well, but if I would specify m as Categorical, the model does not work. What can I do? Within= cv1 cv2 cv3 cv4; between= X1Index AYoS X2index income; CLUSTER=origin; Define: Center cv1 X1Index X2index AYoS (Grandmean); Analysis: TYPE= TWOLEVEL; Estimator= Bayes; fbiteration=10000; Processors=2; MODEL: %Within% y ON cv1 cv2 cv3 cv4; y ON M; !(bw) y M; %Between% M y X2 X1; X1 BY X1Index AYoS; X2 BY income X2index; M ON X1 (a1); M ON X2 (a2); y ON M(b); y ON X1 (c1); y ON IN (c2); X1 with X2; MODEL CONSTRAINT: New(indX1 indX2); indX1=a1*b; indX2=a2*b; |
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We need to see your full output and, preferably, the data as well - send to Support along with your license number. |
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Dear Mr Muthen, thank you for your answer, I have contacted my university because I use a general university access and they do not have a license number that I can use as an individual. Therefore I can not use the support. May I therefore ask a short question of understanding. Do I have to specify a Binary Mediator for a multilevel analysis? Which estimator do I use for this? |
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Q1: Yes. Q2: You can use ML (or MLR) or Bayes or WLSMV. |
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Thank you very much, I appreciate your response. |
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Hi Mplus Team, I have a three-level data-set (individual, team and organization) and I was hoping to test a moderated mediation in which a team level variable (coh) mediates a three-way interaction between two team (Tid and Tdiv) and one organization-level variables (cOid) on an individual outcome (OCB). X Y Z are control variables on the individual level. 1. Is this possible with MPLUS; Type = Threelevel random? Estimator = MLR. 2. Disregarding the model constraints would the below code fit with the description above? MODEL: %WITHIN% OCB ON X Y Z %BETWEEN Tcode% OCB ON coh (b1); OCB ON Tid (cdash); a | coh ON Tid (a1); b | coh ON Tdiv (c1); c | coh ON TdivxTid (c2); %BETWEEN Ocode% coh ON cOid (c6); a ON cOid (c3); b ON cOid (c4); c ON cOid (c5); Thank you in advance for the reply. |
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Yes on both. |
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Great, thank you for the reply! Does this seem accurate in terms of constraints to calculate the indirect effect? MODEL CONSTRAINT: NEW (Low_cOid HI_cOid Low_tdiv HI_tdiv IND_LOWcOidLOWdiv IND_LOWcoidHIdiv IND_HIcOidLOWdiv IND_HIcOidHIdiv); Low_cOid=-1 HI_cOid=1; Low_tdiv=-1; HI_tdiv=1; IND_LOWcOidLOWdiv = a1*b1 + b1*c1*c2*c3*c4*c5*LOW_cOid*LOW_tdiv; IND_LOWcOidHIdiv = a1*b1 + b1*c1*c2*c3*c4*c5*LOW_cOid*HI_tdiv; IND_HIcOidLOWdiv = a1*b1 + b1*c1*c2*c3*c4*c5*HI_cOid*LOW_tdiv; IND_HIcOidHIdiv = a1*b1 + b1*c1*c2*c3*c4*c5*HI_cOid*HI_tdiv; |
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The top 2 levels are similar to twolevel mediation with random slopes so you can check how that is done in our Short Course Topic 7, slides 81 and on. |
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