Intraindividual Dynamic Network of Affects

Linear Autoregressive Mixed-Effects Models for Ecological Momentary Assessment

This repository hosts Jupyter notebooks and Julia code for generating data using exogenous linear autoregressive mixed-effects models (LARMEx) developed as part of DynaMORE projct.

Summary

We consider very simple directed intraindividual networks comprising two symptom nodes and one node for external factors. Assuming intensive longitudinal data through ecological momentary assessment, we formalize the mathematical representation of such networks by LARMEx models. We let every parameter in the model to have fixed and random components aiming at networks that are allowed to have variable structures over reasonable units of time like days or weeks depending on the study design. Then assuming our model is the true data generating process, we simulate data using a predefined set of parameters and investigate the performance and feasibility of this approach in delivering reliable estimates for different choices of the number of observations and the intensity of noise.

How to use these notebooks?

Assuming that you have downloaded the notebookes:

• install Julia from julialang.org
• navigate to the directory of notebooks in Terminal and start Julia
• the prompt at the command line will change to julia> indicating the REPL
• at Julia REPL press ] to enter package manager (prompt changes to pkg>) and execute the following commands
  • activate .
  • instantiate
• this will install all the required packages including IJulia for running the notebooks
• go back to REPL by pressing backspace and run
  • using IJulia makes the package available
  • IJulia.notebook(dir=".") starts a Jupyter dashboard on your default browser
    • the first time you run notebook(), it will prompt you to install Jupyter if it is not found
  • open index.ipynb in Jupyter dashboard and proceed
  • you might need to run using Pkg and then Pkg.build("IJulia") at REPL to complete the setup if you are unable to run the notebook properly
• alternatively you can use REPL without entering the package manager
  • using Pkg
  • Pkg.activate(".")
  • Pkg.instantiate()

It is highly recommended to use a julia environment provided by Project.toml and Manifest.toml as explained earlier. However, one can proceed from scratch by adding the following packages. Then you might need to modify the code and take care of potential version conflicts. Pkg.add(["CSV", "CategoricalArrays", "DataFrames", "Distributions", "IJulia", "Latexify", "LinearAlgebra", "MixedModels", "Printf", "Random"])

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