I want to test a cross-level interaction where I expect the relation of two individual level variables to be moderated by the association of two other variables. This association would be a group level variable (classroom). For instance, if there is a strong positive association between two variables in certain classrooms is the relation btw individual level variables weakened? I don’t know what would be the best way to do this. Can I use an aggregate of correlation as the classroom level moderator variable or is there a better way to do this?
I want to test a cross-level interaction with one level 1 continuous variable and one level 2 continuous variable. I have complex survey data with weight, cluster, stratification, and sub-population. When I try to run the model I receive the following warning and error message:
*** WARNING in ANALYSIS command The INTEGRATION option is not available with this analysis. INTEGRATION will be ignored. *** FATAL ERROR THIS MODEL CAN BE DONE ONLY WITH MONTECARLO INTEGRATION.
I am having trouble figuring out if there is a way to run this model. Below is my model code. Thank you.:
Model: %BETWEEN% bpiint ON c_concdis c_SocCap; s on c_concdis; bpiint WITH s; %WITHIN% s| bpiint on c_NeighAttch; bpiint on RSC_sex RSC_Psych; RSC_sex RSC_Psych c_NeighAttch; Analysis: TYPE = COMPLEX TWOLEVEL RANDOM; ESTIMATOR = MLR; INTEGRATION = MONTECARLO;
Hello I have a cross-level interaction with one level 1 continuous variable and one level 2 continuous variable. In the output, is the between level intercept of s the main effect of my level 1 variable? If not, where is the coefficient for the main effect for my level 1 variable?
Mukadder posted on Wednesday, June 01, 2011 - 6:53 am
Hi Dr Muthéns, I'm trying out a two-level model including upper level mediation (2-2-1 mediation)among three latent variables. I wrote the syntax such that; USEVARIABLES ARE f1 f2 f3; WITHIN = f1; BETWEEN = f2 f3; CLUSTER IS class; ANALYSIS: TYPE = TWOLEVEL RANDOM; MODEL: %WITHIN% f1 ON f2; f1 ON f3; %BETWEEN% f2 ON f3;
Rightfully, the Mplus output gave an error because of the specification of the latents at the levels, specifically f2. Now I'm confused that the output gave me what I intended to do. Because I want to test the effect of f1 on the relationship between f2 and f3. Your help is appreciated...Thanks
I think what you want is the following. You would need to take f1 off of the WITHIN list.
%WITHIN% f1 BY ..... %BETWEEN% f1b BY ... int | f1 XWITH f3; f2 ON f3 int;
Mukadder posted on Wednesday, June 01, 2011 - 12:26 pm
Thank you very much Linda, so happy that this worked! I have a follow up question...I tried a somehow multilevel path model. I created latent variables such that f1 is the sum of correct responses (German achievement), likely f2 (English achievement) and f3 (French achievement. f1 is a within variable; f2 and f3 are between variables. I followed the syntax you suggested to test the effect of f1 on the relationship between f2 and f3. However, Mplus told me that I can't use the XWITH command with the observed variables. In such a situation would the WITH command be more appropriate?
Mukadder posted on Wednesday, June 01, 2011 - 12:29 pm
Sorry I mistyped. The output told me that XWITH is appropriate for only observed variables not latents.
Mukadder posted on Wednesday, June 01, 2011 - 12:44 pm
Linda, I think I have to learn how to read before how to use Mplus! The output for my trial multilevel path model says:
The XWITH option is not available for observed variable interactions. Use the DEFINE command to create an interaction variable. Problem with: INT | f1 XWITH f3