

Crossdomain versus parallel processe... 

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I am currently working on a model with four time points in which there are two latent variables. In the model, the intercept of variable 1 is predicting the intercept of variable 2, and the slope/change of variable 1 is predicting the slope/change of variable 2. However, I am uncertain of the type of model I should be using. From what I understand, parallel processes latent growth curve models seem to involve two growth curves that are interdependent whereas crossdomain deals with the relationships between two processes that are occuring over the same time period. Both of these sound like they could define my model. Is there something that I am missing? What are the differences between these two types of models? I am sure that there are some very distinct differences between the two types, but I cannot seem to find anything comparing the two. Thank you in advance. 


In the terminology that I am used to, I would call the first model that you describe a sequential process growth model where the first process is measured earlier than the second process. A parallel growth model is one where the processes are measured at the same time. Other than that the models are similar. I think what you refer to as a crossdomain model is a parallel growth model from what you say. 

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