You have input in the FAQ Latent variable interaction LOOP plot.
Moderation modeling with latent variables and dummy Xs may be more easily done via multiple-group modeling (3 groups in your case) where key parameters vary across the groups. But you can use XWITH also for interactions between latents and dummies.
Modeling the moderation between M and Y requires extra care as shown in Model 1 of Preacher, Rucker, Hayes (2007) in MBR.
From Preacher, Rucker, Hayes (2007), I want Model 2 and Model 3. Previously, I used "Define: MV = M * V with continuous observed variables. Now "Define" does not work before "Model" since M and V are latent variables created by "BY".
I can only get XWITH to work for "Type = Random; Algorithm = Integration;", no bootstrapping or fit stats. Is there a better alternative? I appreciate your assistance.
MODEL: Variety BY Variety1 Variety2 Variety3; !(M) Expertis BY Chooser1 Chooser2 Chooser3; !(W) SelfDet BY SelfDet1 SelfDet2 SelfDet3 SelfDet4; PrefID BY Manchk1 ManChk2 ManChk3; Inter| Expertis XWITH Variety; !(M * W) Variety ON Cat_0 Cat_U (a1); !(a1 or M on X1 and X2) Satisf1 ON Cat_0 Cat_U !(c' or Y on X! and X2) Variety (b1) Expertis !(b2) Inter (b3) SelfDet PrefID; !Expertis WITH Variety; !Inter WITH Variety; MODEL CONSTRAINT: PLOT(Indirect); LOOP(Expert,-2,2,0.1); Indirect=a1*(b1+b3*Expert); !(Y = a1(b1+b3W)) !MODEL INDIRECT: !Cat_0 IND Variety Satisf1; !Cat_U IND Variety Satisf1;
I see that the User Guide explains that. I was hoping for an alternative.
I have a working model, output and plots but I see that the model fit statistics are limited with MLR.
The plot of indirect effect against values of the moderator shows confidence intervals, that always include 0 so I can interpret that as meaning that the the null H of "zero indirect effect regardless of the level of the moderator" cannot be rejected. Still I was wondering if you could direct me to a source that would explain how to interpret the output.
One of the interaction variables is latent so I use XWITH and Type=Random.
I receive the error message "*** ERROR MODEL INDIRECT is not available for TYPE=RANDOM.
Variety BY Variety1 Variety2 Variety3; !(M) Expertis BY Chooser1 Chooser2 Chooser3; !(W) Inter| NumCat_3 XWITH Expertis; !(X * W) Variety ON NumCat_3 (a1)!(M on X1) Expertis (a2) !(M on W) Inter (a3); !(M on XW) Satisf1 ON NumCat_3 (c) Variety (b1); !(Y on X, M)
MODEL CONSTRAINT: PLOT(Indirect); LOOP(Expert,0,7,0.1); Indirect=(a1+a3*Expert)*b1;!(a1+a3W)b1
Thank you for all of your help you have been very responsive and helpful. MPlus is awesome.
I have the analysis I needed including the CI, plot and plot data.
As well as being SEM rather than regression and modelling latent variables, with the LOOP, MPlus is superior to running Process regressions many times with transformed IV and Moderator values as suggested in Spiller et al. JMR 2013. As an enhancement I was hoping for p-values over the range of values of the moderator in the loop plot.
Also, it looks like there's no way to get bootstrap CI. Please confirm 1. With Latent moderators, I have to use XWITH 2. With XWITH, I must use Type=Random 3. With Type=Random, Bootstrap is currently unavailable.
Hello, When I run the input below I get the following error message: "A parameter label has been redeclared in MODEL CONSTRAINT. Problem with: IND". Do I need to provide another label for the plot command? Here is my input:
MODEL: sse by smq12 smq21 smq24 smq28 smq29; pap by agq2 agq4 agq8; procp by passp1-passp3; anx by smq4 smq6 smq13 smq14 smq18; procp on gpa gender; procp on anx (b); anx on sse pap (a); procp on pap; interact | sse xwith pap; anx on interact(c); sse pap anx;
model constraint: new(ind wmodval); wmodval=.444;!+1SD sse ind=(a+c*wmodval)*b; plot(ind); loop(sse,-.444,.444,0.01);