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bayest: An R Package for Effect-Size Targeted Bayesian Two-Sample t-Tests Cover

bayest: An R Package for Effect-Size Targeted Bayesian Two-Sample t-Tests

By: Riko Kelter  
Open Access
|Jun 2020

References

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  2. Kruschke, J K 2018 Rejecting or Accepting Parameter Values in Bayesian Estimation. Advances in Methods and Practices in Psychological Science, 1(2): 270280. DOI: 10.1177/2515245918771304
  3. Cohen, J 1988 Statistical Power Analysis for the Behavioral Sciences. 2nd edition. Hillsdale, N. J.: Routledge. ISBN 978-0-8058-0283-2. DOI: 10.1186/s12874-020-00968-2
  4. Kelter, R 2020 Analysis of Bayesian posterior significance and effect size indices for the two-sample t-test to support reproducible medical research. BMC Medical Research Methodology, 20(88). DOI: 10.1214/ss/1177011136
  5. Kelter, R 2019 A new Bayesian two-sample t-test for effect size estimation under uncertainty based on a two-component Gaussian mixture with known allocations and the region of practical equivalence. arXiv preprint. https://arxiv.org/abs/1906.07524v2.
  6. Gelman, A and Rubin, D B 1992 Inference from Iterative Simulation Using Multiple Sequences. Stat. Sci., 7(4): 457472.
DOI: https://doi.org/10.5334/jors.290 | Journal eISSN: 2049-9647
Language: English
Submitted on: Aug 6, 2019
Accepted on: May 14, 2020
Published on: Jun 15, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2020 Riko Kelter, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.