

Multilevel mediation with count outcome 

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I want to test indirect effects in a 111 multilevel mediation model with a count outcome. The Mplus syntax I've put together runs, but I'm not sure it is correct. I'm writing for guidance on (1) if the syntax (below) seems OK, (2) if Mplus can be used to generate confidence intervals for the indirect effect using bootstrapping or Monte Carlo methods. Here's the syntax (X = predictor, M = mediator, Y = outcome) USEVARIABLES ARE X M Y ; CLUSTER IS ID; COUNT IS Y (nb); MISSING = ALL (99); ANALYSIS: ESTIMATOR IS MLR; TYPE = TWOLEVEL RANDOM; MODEL: %WITHIN% X*; Y ON X* (cw) M* (bw) ; M ON X* (aw) ; %BETWEEN% B_X BY X@1; X@0 B_X*; ! [X@0 B_X*]; B_M BY M@1; M@0 B_M*; [M@0 B_M*]; Y*; [Y*]; Y ON B_X* (cb) B_M* (bb); B_M ON B_X* (ab); MODEL CONSTRAINT: NEW(indb indw totalw totalb); indw=aw*bw; indb=ab*bb; totalw = indw + cw; totalb = indb + cb; Thanks, Jon 


The a*b product formulas are not suitable for count outcomes. See our Short Course video and handout for Topic 11 on our website and also Chapter 8 of our RMA book. 

Noah Emery posted on Friday, August 30, 2019  11:27 am



I noticed that Mplus version 8 now allows standardized effects to be estimated for models with count outcomes (e.g., stdYX), but I cannot find any documentation regarding how these is handled computationally. Are these estimates trustworthy? 


For counts, standardization with respect to the X's is the only one that makes sense. You can obtain this by simply standardizing your continuous X's. Binary X's should not use standardized coefficients. 

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