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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? |
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Cross-level interactions are specified as random slopes in Mplus. See Example 9.2 and slide 43 of the Topic 7 course handout for details. |
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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; |
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I am sorry, I realized I should have been more clear in my original post. I originally tried running the model with simply Analysis: TYPE = COMPLEX TWOLEVEL RANDOM; But I got the same fatal error message. Thank you, Ayesha |
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Try adding ALGORITHM=INTEGRATION; to the ANALYSIS command. If that does not help, please send the full output and your license number to support@statmodel.com. |
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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? Thank you, Ayesha |
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Yes. |
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Mukadder posted on Wednesday, June 01, 2011 - 6:53 am
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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 |
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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; |
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Mukadder posted on Wednesday, June 01, 2011 - 12:26 pm
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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? |
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Mukadder posted on Wednesday, June 01, 2011 - 12:29 pm
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Sorry I mistyped. The output told me that XWITH is appropriate for only observed variables not latents. Thanks again. |
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Mukadder posted on Wednesday, June 01, 2011 - 12:44 pm
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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 |
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Yes, so use the DEFINE command to create the interaction instead of the XWITH option. |
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Ahmad Adeel posted on Thursday, June 30, 2016 - 10:07 am
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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) PIJ 16 |
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Ahmad Adeel posted on Thursday, June 30, 2016 - 11:18 am
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in the above problem pij (level 2) is an interaction of pp (level 1) and a moderator (level 2). |
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When you multiply a level 1 and a level 2 variable, the resulting variable is a level 1 variable, that is, it will vary within clusters. |
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Thanks a lot, as you said, multiplying a level 1 and level 2 will make a level 1 variable only, then how can we check the moderation effect if IV and DV are on level 1 and Moderator is at level 2? |
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Instead of %within% s | toi on pp; %between% toi s on pij; you should have %within% s | toi on pp; %between% toi s on w; where w is the level-2 moderator. This implies the desired product of pp and w. |
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Ahmad Adeel posted on Saturday, July 02, 2016 - 4:26 am
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Thanks a lot, it worked. |
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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 |
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If a variable on on the WITHIN list, it cannot be used in the between part of the model. |
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