EcoApps_Random_Effects

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EcoApps_Random_Effects

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Supplemental data and code files for "Ensuring identifiability in hierarchical mixed effects Bayesian models" by Kiona Ogle and Jarrett Barber, published in Ecological Appilcations.

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# READ-ME / OVERVIEW

The data and code provided here accompay the paper "Ensuring identifiability in hierarchical mixed effects Bayesian models" 
by Kiona Ogle and Jarrett Barber, published in Ecological Appilcations. The following R files are provided:

0) **EcoApps supplemental materials.pdf** -- PDF with detailed supplemental materials, including Figs. S1-S6, Tables S1 and S2, and Sections S1-S6, where the Sections summarize data and code used, and the actual data and code files are provided here, on Github, as R and Stan files, including:
1) **Data S1.RData** -- Contains the simulated data that are used with the models implemented via "Code A2.R" and "Code A3.R" (see also, Section S1 in **EcoApps supplemental materials.pdf**).
2) **Code A2.R** -- R script code for implementing the random effect regression summarized in Equation 5 in the manuscript, which loads and prepares data and implements the model(s) in JAGS. The code does not implement any reparameterization or computational solutions to solving the non-identifiabilty of the overall intercept and random effects terms, but it does include options for specifying a relatively non-informative Gamma prior or a weakly informative folded-Cauchy prior for the random effects variance-related parameter. The model is applied to the three datasets contained in the “Data S1.RData” object (see also, Section S2 in **EcoApps supplemental materials.pdf**).
3) **Code A3.R** -- R script code for implementing Solutions 1 (hierarchical centering, HC), 2 (sum-to-zero, SZ), and 4 (post-sweeping, PS) with the random effect regression summarized in Equation 5 in the manuscript (see also, Section S3 in **EcoApps supplemental materials.pdf**)..
4) **Code A4.R** -- R script code for implementing Solutions 1 (HC), 2 (SZ), and 4 (PS) with the nested random effects regression summarized in Equation 11 in the manuscript (see also, Section S4 in **EcoApps supplemental materials.pdf**)..
5) **Code A5.R** -- R script code for implementing Solutions 2 (SZ) and 4 (PS) with the Bayesian regression involving crossed random effects, as summarized in Equation 14 in the manuscript (see also, Section S5 in **EcoApps supplemental materials.pdf**)..
6) **stanwork.V2.R** -- R script for running the models in Stan (see also, Section S6 in **EcoApps supplemental materials.pdf**).
7) **S2.v2.stan** -- Stan code for the models (see also, Section S6 in **EcoApps supplemental materials.pdf**).

Please also see the **License** file for "instructions" on how the materials/files posted here can be reused.

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