Prior choice and data requirements of Bayesian multivariate mixed effects models fit to tag-recovery data: The need for power analyses

1. Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag-recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect non-zero correlations has rarely been evaluated and these few studies have not focused on tag-recovery data, which is a common data type.
2. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (Anas platyrhychos) tag-recovery dataset and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for t..., , Instructions and metadata are provided at the top of each R script, including required R packages listed at the top of individual R scripts. Software specifications are included in the README file included in the data files.
This Dryad repository is for two manuscripts:

Deane, C. E., L. G. Carlson, C. J. Cunningham, P. Doak, K. Kielland, and G. A. Breed. 2023. Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag-recovery data: The need for power analyses. Ecology and Evolution 13:e9847. https://doi.org/10.1002/ece3.9847 Note: R scripts specific to the power analysis in this manuscript begin with \"P\"

Deane, C. E., L. G. Carlson, C. J. Cunningham, P. Doak, K. Kielland, and G. A. Breed. In prep. Accurately estimating correlations between demographic parameters: a response to Riecke et al. (in press). Ecology and Evolution Note: New R scripts specific to our response begin with the letter \"R\" 

, # Data for the article \"Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag-recovery data: the need for power analyses\"

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# Reference information

* File name: README_Dataset-PriorsDataRequirementsBayesianHierarchicalModels.md
* Authors: C.E. Deane ([[e-mail]](mailto:[e-mail]))
* Other contributors: L.G. Carlson, C.J. Cunningham, P. Doak, K. Kielland, G.A. Breed.
* Date of Issue: 2023-02-15
* Suggested Citations:
* Dataset citation:
> Deane, C.E., L.G. Carlon, C.J. Cunningham, P. Doak, K. Kielland, and G.A. Breed. 2023. Data for \"Prior choice and data requirements of Bayesian multivariate hierarchical models fit to tag-recovery data: the need for power analyses\", Dryad, Dataset, [https://doi.org/10.5061/dryad.hmgqnk9h6](https://doi.org/10.5061/dryad.hmgqnk9h6)
* Software citation:
> Deane, C.E., L.G. Carlon, C.J. Cunningham, P. Doak, K. Kielland, and G.A. Breed. 2023. Software for \"...