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Dear. Dr. Muthen, is it possible to estimate effects from a within level variable to a between level variable (random slope) with Mplus. My case is the following: 2 level panel data (between N = 31), 2 waves. I am using a latent difference score approach to model the change of a dep. variable Y. My hypothesis is, that the change at the between level is affected by an interaction of Y at time 1 (within) and an indep. var X (within). Best regards Christoph Weber 


Example 9.2 shows a random slope model. 


Thanks, but is it possible to specify: %within% s  y ON x w; xw  x xwith w; %BETWEEN% y s ON w x xw; 


Your specification is not allowed and is not the way to obtain a crosslevel interaction between x and w. Example 9.2 is the way to do that. To see how the formulas work, see Slide 45 of the Topic 7 course handout on the website. 


Thanks, I know that this is not a common multilevel model. But actually my hypothesis is, that individual factors (and their interaction) have an effect on the development on cluster level. Do you have any ideas how to model this? Thanks Christoph Weber 


Typically you want the between part of the subjects' scores to influence a clusterlevel (betweenlevel) DV, but it sounds like that's not what you are after. It sounds like you somehow want the withincluster part of a subject's score to influence a clusterlevel DV  is that right? Could this be an example: If a student misbehaves much more than the classroom average, this influences the teacher's wellbeing? If so, I have not seen this attempted in multilevel modeling  someone else? 


I have the following design. 31 classes, 2 measures and an intervention between T1 and T2 that should change the environmental consciousness (EC). The EC are measured at T1 and T2. Further I have a measure of social capital at T1. The hypothesis is, that in those classes, where students with high social capital have a low EC, there should be a worsening of EC on class level. Thus I thought it would be necessary to model an interaction effect of social capital and EC on the change of EC on class level. 


I think you can use regular multilevel modeling to accomplish this. You need a betweenlevel interaction for the latent betweenlevel parts (random intercepts) of ec and sc (social capital). In Mplus terms you say: . . . cluster = classrm; ! ec and sc are allowed to vary on both !within and between, so not on Within= or !Between= lists Analysis: Type = twolevel; Model: %between% int  ec1 xwith sc; ec2 on ec1 sc int; %within% ec2 on ec1 sc; ec1 with sc; 


Many thanks for your help! Christoph Weber 

Dave posted on Thursday, February 23, 2012  12:32 pm



Building on this series of postings, I am interested in crosslevel interactions between within and between level variables. I am interested in testing a model similar to example 9.5 (below) in the version 6, April 2010 user guide. I have dropped x1 from the model to simplify the example. VARIABLE: NAMES ARE y1 y2 x2 w clus; WITHIN = x2; BETWEEN = w; CLUSTER IS clus; ANALYSIS: TYPE = TWOLEVEL RANDOM; MODEL: %WITHIN% s2  y2 ON y1; y2 ON x2; s1  y1 ON x2; %BETWEEN% y1 y2 s1 s2 ON w; As I understand this example, it is testing crosslevel interactions between x2 and w predicting the mediating variable y1 and between y1 and w predicting y2. x2, y1 and y2 are at the within level. I am wondering if it is possible to adapt this model to accomodate y1 at the between level rather than at the within level. The moderating variable w would remain at the between level and the crosslevel interaction would be between x2 and w predicting betweenlevel y1 and y1 and w predicting y2. If this is possible, how would I adapt the code? Thanks in advance for your assitance. 


A crosslevel interaction is due to a random slope. If y1 is between only, it cannot have a random slope. You can have an interaction between x2 and w influencing the betweenlevel y1 if x2 has betweenlevel variation. If that betweenlevel variation is latent, you use XWITH. 

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