I want to analyze my data using a repeated measures logistic regression in a SEM framework. I assessed my categorical dependent variable (cooperation: yes vs. no) twice, namely in two different games that vary according to a within-subjects manipulation (independent variable 1, categorical). Now, I want to test whether a personality characteristic (between-subjects, latent factor) predicts cooperation in one game, but not the other. That is, I want to directly test the hypothesized interaction effect between personality and cooperation in the different games. Can you help me how to model this in Mplus? Unfortunately, I have not yet found a solution on my own.
You cannot regress a within-level variable on a between-level variable except by using a random slope as shown in Example 9.2. You can regress the between-part of the within-level variable on a between-level variable as shown in Example 9.1.
Thank you very much for your helpful response. The model worked fine with an observed cluster-level covariate. However, is there also an opportunity to include a latent cluster-level variable that is modeled based on multiple items?
Thank you very much for the information. It worked!
However, one question still remains: I tried the model with the following specification
y WITH s;
as suggested in the User's Guide Example 9.2. In this case, I get an error message telling me that I have a non-positive definite first-order derivative product matrix. This problem is due to parameter 6 which corresponds to the error variance (psi matrix) of y. In case I do not allow y to be correlated with s (thus omitting the statement 'y with s;'), this error message does not occur.
Can you tell me what this means for the interpretation of my results?
Hello I figure I would jump in here as I am trying to recreate an repeated measures logistic regression analysis done with the SAS GLIMMIX Macro in Mplus.
What I have is data gathered at random time points using ecological momentary assessment. My dependent variable is the presence or absence of cues for drug use. The IV is amount of time till the next use of a substance (in hour bins from 1-5). I am examining if there is a linear trend to increased likelihood of the cue being present as one gets closer to the use event. As this is a reanalysis of published data there should be. I've been trying various examples but I keep getting stuck. bill