Resources for DSEM

General
1

Hello!

I am new to Bayesian inferencing, and my thesis has grown to require some advanced modeling techniques that I am a little out of depth in performing.

To give a general outline, I have performed an ecological trophic mesocosm study that we sampled across time, collecting multiple metrics regarding the movement of biomass across our model food web.

Just from exploratory analysis and trial models I am dealing with….

  1. Random effects regarding our mesocosms
  2. Autoregressive structure with each of our biomass markers
  3. Vector Autoregressive structure with our biomass markers (e.g. Algal biomass at a previous time point influencing grazing biomass at current time)
  4. The need for a structural equation model to best capture the relationships of the food web.

I was looking for some resources so I could build up a model that captures the four points (i.e. Dynamic Structural Equation Model) I wish to implement. I have not had any luck with my searches,and was hoping the trove of knowledge here might yield some better results.

A preemptive thank you!

2

You might look at the blavaan package.

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3

Following on Solomon’s comment. Depending on how you want to specify the model, blavaan or ctsem , are good options that specify longitudinal SEM models, and use Stan in the back

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If you’re interested in D-SEM models with Stan, you might find the implementations in this repository really useful. It includes explanatory presentations comparing their implementation against Mplus, and provides R scripts as a tutorial (in fact, I think they are still writing a tutorial paper with all this content).

You may also find usefull this tutorial paper about several longitudinal models (e.g., ARMA, DSEM, DLCSEM…) useful, although they use JAGS rather than Stan (see its repository).

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