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 cross-domain 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 cross-domain model is a parallel growth model from what you say.