Random Slopes in SEM and Plots PreviousNext
Mplus Discussion > Structural Equation Modeling >
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 Anonymous posted on Sunday, May 01, 2005 - 6:52 am
Is it possible to graph the random slopes in an SEM? For example, my model is similar to example 5.13 in the user's guide. I was wondering of PLOT3 will do this or if there is something special that I had to do?

Thank you in advance
 bmuthen posted on Sunday, May 01, 2005 - 4:45 pm
You can request factor score estimates and use PLOT3 to show their distribution univ and bivariate with another variable.
 Anonymous posted on Tuesday, May 03, 2005 - 4:21 am
Thank you so much!
 Paul R. Hernandez posted on Thursday, May 12, 2011 - 8:24 am
Question:
Is there any way to avoid listwise deletion when using random slopes analysis?

My situation:
I have 2 correlated outcomes of interest DV1 & DV2 (about 25% of DV2 are missing)
I have 2 uncorrelated predictors IV1 & IV2 (about 25% of IV2 are missing).

My model is:
s1 | DV1 on IV1 ;
s2 | DV2 on IV2 ;

The problem:
Any instances where the either DV2 or IV2 are missing, those cases get deleted.

thanks for you help!
 Linda K. Muthen posted on Thursday, May 12, 2011 - 9:19 am
I have no idea what version of Mplus you are using but in the current version, TYPE=MISSING is the default so cases with missing on DV2 will not be eliminated. However, cases with missing on one or more independent variables will be deleted because missing data theory does not apply to independent variables.
 Paul R. Hernandez posted on Thursday, May 12, 2011 - 10:01 am
Thanks!
 Mireille H. posted on Tuesday, December 20, 2011 - 4:28 am
Dear Mr./Mrs. Munthén

The M-plus output (version 6) indicated that a few of my 3-way interaction terms were significant, and I was wondering how I can test wich slopes of each term significantly differ from each other? I tried to use the online calculator of Mr. Preacher for this, but this gave me unplausible results. I hope you can help me with this.

Kind regards
 Linda K. Muthen posted on Tuesday, December 20, 2011 - 1:31 pm
You can use the Wald test or difference testing. See MODEL TEST for the Wald test. This assumes the coefficients being compared are on the same scale.
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