bayesassurance: An R Package for Calculating Sample Size and Bayesian Assurance

In this paper, we present bayesassurance, an R package designed for computing Bayesian assurance criteria which can be used to determine sample size in Bayesian inference setting. The functions included in the R package offer a two-stage framework using design priors to specify the population from which the data will be collected and analysis priors to fit a Bayesian model. We also demonstrate that frequentist sample size calculations are exactly reproduced as special cases of evaluating Bayesian assurance functions using appropriately specified priors.

Jane Pan (University of California, Los Angeles) , Sudipto Banerjee (University of California, Los Angeles)
2023-12-18

0.1 Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-066.zip

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References

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Citation

For attribution, please cite this work as

Pan & Banerjee, "bayesassurance: An R Package for Calculating Sample Size and Bayesian Assurance", The R Journal, 2023

BibTeX citation

@article{RJ-2023-066,
  author = {Pan, Jane and Banerjee, Sudipto},
  title = {bayesassurance: An R Package for Calculating Sample Size and Bayesian Assurance},
  journal = {The R Journal},
  year = {2023},
  note = {https://doi.org/10.32614/RJ-2023-066},
  doi = {10.32614/RJ-2023-066},
  volume = {15},
  issue = {3},
  issn = {2073-4859},
  pages = {138-158}
}

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