Computing analytic Bayes factors from summary statistics in repeated-measures designs
References
- Berger J.O., Sellke T. (1987): Testing a point null hypothesis: The irreconcilability of p values and evidence. Journal of the American Statistical Association 82(397): 112.
- Bortolussi M., Dixon P. (2002): Psychonarratology: Foundations for the Empirical Study of Literary Response. Cambridge University Press.
- Campbell J.I.D., Thompson V.A. (2012): MorePower 6.0 for ANOVA with relational confidence intervals and bayesian analysis. Behavior Research Methods 44(4): 1255–1265.
- Faulkenberry T.J. (2018): Computing Bayes factors to measure evidence from experiments: An extension of the BIC approximation. Biometrical Letters 55(1): 31–43.
- Faulkenberry T.J. (2019): Estimating evidential value from analysis of variance summaries: A comment on Ly et al. (2018). Advances in Methods and Practices in Psychological Science.
- Faulkenberry T.J. (2020): Estimating Bayes factors from minimal summary statistics in repeated measures analysis of variance designs. Advances in Methodology and Statistics 17(1).
- Faulkenberry T.J. (2021): The Pearson Bayes factor: An analytic formula for computing evidential value from minimal summary statistics. Biometrical Letters 58(1): 1–26.
- Fayol M., Thevenot C. (2012): The use of procedural knowledge in simple addition and subtraction problems. Cognition 123(3): 392–403.
- Fisher R.A. (1925): Statistical Methods for Research Workers. Oliver & Boyd, Edinburgh.
- García-Donato G., Sun D. (2007): Objective priors for hypothesis testing in oneway random effects models. Canadian Journal of Statistics 35(2): 303–320.
- Gigerenzer G. (2004): Mindless statistics. The Journal of Socio-Economics 33(5): 587–606.
- Kass R.E., Raftery A.E. (1995): Bayes factors. Journal of the American Statistical Association, 90(430): 773–795.
- Ly A., Raj A., Etz A., Marsman M., Gronau Q.F., Wagenmakers E.-J. (2018): Bayesian reanalyses from summary statistics: A guide for academic consumers. Advances in Methods and Practices in Psychological Science, 1(3): 367–374.
- Masson M.E.J. (2011): A tutorial on a practical Bayesian alternative to null-hypothesis significance testing. Behavior Research Methods 43(3): 679–690.
- Nathoo F.S., Masson M.E. (2016): Bayesian alternatives to null-hypothesis significance testing for repeated-measures designs. Journal of Mathematical Psychology 72: 144–157.
- Raftery A.E. (1995): Bayesian model selection in social research. Sociological Methodology 25: 111–163.
- Rouder J.N., Morey R.D., Speckman P.L., Province J.M. (2012): Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5): 356–374.
- Schwarz G. (1978): Estimating the dimension of a model. The Annals of Statistics 6(2): 461–464.
- Sellke T., Bayarri M.J., Berger J.O. (2001): Calibration of p-values for testing precise null hypotheses. The American Statistician 55(1): 62–71.
- Thiele J.E., Haaf J.M., Rouder J.N. (2017): Is there variation across individuals in processing? Bayesian analysis for systems factorial technology. Journal of Mathematical Psychology 81: 40–54.
- Wagenmakers E.-J. (2007): A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review 14(5): 779–804.
- Wang M., Sun X. (2014): Bayes factor consistency for one-way random effects model. Communications in Statistics – Theory and Methods, 43(23): 5072–5090.
Language: English
Page range: 1 - 21
Published on: Jun 28, 2023
Published by: Polish Biometric Society
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Related subjects:
© 2023 Thomas J. Faulkenberry, Keelyn B. Brennan, published by Polish Biometric Society
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.