rmBayes-package: The 'rmBayes' package.
In rmBayes: Performing Bayesian Inference for Repeated-Measures Designs
rmBayes-package R Documentation
The 'rmBayes' package.
Description
Performing Bayesian Inference for Repeated-Measures Designs
A Bayesian credible interval is interpreted with respect to posterior probability,
and this interpretation is far more intuitive than that of a frequentist confidence interval.
However, standard highest-density intervals can be wide due to between-subjects variability and tends
to hide within-subject effects, rendering its relationship with the Bayes factor less clear
in within-subject (repeated-measures) designs.
This urgent issue can be addressed by using within-subject intervals in within-subject designs,
which integrate four methods including the Wei-Nathoo-Masson (2023) doi:10.3758/s13423-023-02295-1,
the Loftus-Masson (1994) doi:10.3758/BF03210951,
the Nathoo-Kilshaw-Masson (2018) doi:10.1016/j.jmp.2018.07.005,
and the Heck (2019) doi:10.31234/osf.io/whp8t interval estimates.
Author(s)
Maintainer: Zhengxiao Wei zhengxiao@uvic.ca (ORCID)
Authors:
Farouk S. Nathoo nathoo@uvic.ca (ORCID)
Michael E. J. Masson mmasson@uvic.ca (ORCID)
References
Heck, D. W. (2019). Accounting for estimation uncertainty and shrinkage in Bayesian within-subject intervals: A comment on Nathoo, Kilshaw, and Masson (2018). Journal of Mathematical Psychology, 88, 27–31.
Loftus, G. R., & Masson, M. E. J. (1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin & Review, 1, 476–490.
Nathoo, F. S., Kilshaw, R. E., & Masson, M. E. J. (2018). A better (Bayesian) interval estimate for within-subject designs. Journal of Mathematical Psychology, 86, 1–9.
Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374.
Stan Development Team (2024). RStan: the R interface to Stan. R package version 2.32.5 https://mc-stan.org
Wei, Z., Nathoo, F. S., & Masson, M. E. J. (2023). Investigating the relationship between the Bayes factor and the separation of credible intervals. Psychonomic Bulletin & Review, 30, 1759–1781.
See Also
Useful links:
rmBayes documentation built on May 29, 2024, 2:36 a.m.
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| rmBayes-package | R Documentation |
The 'rmBayes' package.
Description
Performing Bayesian Inference for Repeated-Measures Designs
A Bayesian credible interval is interpreted with respect to posterior probability, and this interpretation is far more intuitive than that of a frequentist confidence interval. However, standard highest-density intervals can be wide due to between-subjects variability and tends to hide within-subject effects, rendering its relationship with the Bayes factor less clear in within-subject (repeated-measures) designs. This urgent issue can be addressed by using within-subject intervals in within-subject designs, which integrate four methods including the Wei-Nathoo-Masson (2023) doi:10.3758/s13423-023-02295-1, the Loftus-Masson (1994) doi:10.3758/BF03210951, the Nathoo-Kilshaw-Masson (2018) doi:10.1016/j.jmp.2018.07.005, and the Heck (2019) doi:10.31234/osf.io/whp8t interval estimates.
Author(s)
Maintainer: Zhengxiao Wei zhengxiao@uvic.ca (ORCID)
Authors:
Farouk S. Nathoo nathoo@uvic.ca (ORCID)
Michael E. J. Masson mmasson@uvic.ca (ORCID)
References
Heck, D. W. (2019). Accounting for estimation uncertainty and shrinkage in Bayesian within-subject intervals: A comment on Nathoo, Kilshaw, and Masson (2018). Journal of Mathematical Psychology, 88, 27–31.
Loftus, G. R., & Masson, M. E. J. (1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin & Review, 1, 476–490.
Nathoo, F. S., Kilshaw, R. E., & Masson, M. E. J. (2018). A better (Bayesian) interval estimate for within-subject designs. Journal of Mathematical Psychology, 86, 1–9.
Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56, 356–374.
Stan Development Team (2024). RStan: the R interface to Stan. R package version 2.32.5 https://mc-stan.org
Wei, Z., Nathoo, F. S., & Masson, M. E. J. (2023). Investigating the relationship between the Bayes factor and the separation of credible intervals. Psychonomic Bulletin & Review, 30, 1759–1781.
See Also
Useful links:
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