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
Yes, so use the DEFINE command to create the interaction instead of the XWITH option.
Ahmad Adeel posted on Thursday, June 30, 2016 - 10:07 am
Hello I am trying a cross level interaction as described in example 9.2. but when in try to run the model, I receive the error, please guide. Thanks.
My code--- usevariables are tn,pp,toi,pij; within are pp; between are pij; cluster is tn; CENTERING is GRANDMEAN (pp); analysis: type = twolevel random; model: %within% s | toi on pp; %between% toi s on pij; toi with s;
Error message---- *** ERROR One or more between-level variables have variation within a cluster for one or more clusters. Check your data and format statement.
Between Cluster ID with variation in this variable Variable (only one cluster ID will be listed)
Ahmad Adeel posted on Thursday, June 30, 2016 - 11:18 am
in the above problem pij (level 2) is an interaction of pp (level 1) and a moderator (level 2).
Hi, I am going to test a two-level first stage moderated mediation.
But when I tried to run the analysis, I received some errors and failed to produce the result. Could you help?
MISSING = all (999); USEVARIABLES ARE x m w y;
CLUSTER IS group; WITHIN = x m; BETWEEN = w; DEFINE: CENTER x(GROUPMEAN); CENTER m(GROUPMEAN); CENTER w(GRANDMEAN); ANALYSIS: TYPE = TWOLEVEL RANDOM; MODEL:
%WITHIN% S | m on x; y on m(b) x;
%BETWEEN% S on w(a1); [S](a0); m with S; y with S; y with m; y with w;
MODEL CONSTRAINT: NEW (ind_h ind_l); ind_h=(a0+a1*(0.33))*b; ind_l=(a0-a1*(0.33))*b;
OUTPUT: SAMPSTAT; CINTERVAL;
*** ERROR in MODEL command Within-level variables cannot be used on the between level. Within-level variable used: M *** ERROR in MODEL command Within-level variables cannot be used on the between level. Within-level variable used: M *** ERROR The following MODEL statements are ignored: * Statements in the BETWEEN level: M WITH S Y WITH M