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Results: 60
Number of items: 60
  • Open Access
    van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Stefan, A., Voelkel, J. G., & Wagenmakers, E.-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28(3), 813–826. https://doi.org/10.3758/s13423-020-01798-5
  • Open Access
    van Doorn, J. B. (2021). Bayes factor hypothesis tests for ranks and researchers. [Thesis, fully internal, Universiteit van Amsterdam].
  • Giolla, E. M., & Ly, A. (2020). What to do with all these Bayes factors: How to make Bayesian reports in deception research more informative. Legal and Criminological Psychology, 25(2), 65-71. https://doi.org/10.1111/lcrp.12162
  • van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E.-J., Derks, K., Dablander, F., Gronau, Q. F., Kucharský, Š., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Voelkel, J. G., Stefan, A., Ly, A., Hinne, M., Matzke, D., & Wagenmakers, E.-J. (2020). A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP. Année Psychologique, 120(1), 73-96. https://doi.org/10.31234/osf.io/spreb, https://doi.org/10.3917/anpsy1.201.0073
  • Hutton, J. L., Diggle, P. J., Bird, S. M., Hennig, C., Longford, N., Mathur, M. B., Vander Weele, T. J., Ioannidis, J. P. A., Chai, C. P., Dowe, D. L., Ferguson, J., Fitz-Simon, N., Friede, T., Rover, C., Grieve, A. P., Kumar, K., Ly, A., Mansmann, U., Mateu, J., ... Held, L. (2020). Discussion on the meeting on ‘Signs and sizes: understanding and replicating statistical findings’. Journal of the Royal Statistical Society. Series A (Statistics in Society), 183(2), 449-469. https://doi.org/10.1111/rssa.12544
  • Open Access
    Gronau, Q. F., Ly, A., & Wagenmakers, E.-J. (2020). Informed Bayesian t-Tests. American Statistician, 74(2), 137-143. https://doi.org/10.1080/00031305.2018.1562983
  • Open Access
    Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharský, S., Derks, K., Gronau, Q. F., Raj, A., Boehm, U., van Kesteren, E.-J., Hinne, M., Matzke, D., Marsman, M., & Wagenmakers, E.-J. (2020). The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test. Computational Brain & Behavior, 3(2), 153-161. https://doi.org/10.31234/osf.io/dhb7x, https://doi.org/10.1007/s42113-019-00070-x
  • Open Access
    Landy, J. F., Jia, M. L., Ding, I. L., Viganola, D., Tierney, W., Dreber, A., Johannesson, M., Pfeiffer, T., Ebersole, C. R., Gronau, Q. F., Ly, A., van den Bergh, D., Marsman, M., Derks, K., Wagenmakers, E.-J., Proctor, A., Bartels, D. M., Bauman, C. W., Brady, W. J., ... Uhlmann, E. L. (2020). Crowdsourcing hypothesis tests: Making transparent how design choices shape research results. Psychological Bulletin, 146(5), 451-479. https://doi.org/10.1037/bul0000220
  • Open Access
    van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman’s ρ. Journal of Applied Statistics, 47(16), 2984-3006. https://doi.org/10.1080/02664763.2019.1709053
  • Open Access
    Faulkenberry, T. J., Ly, A., & Wagenmakers, E.-J. (2020). Bayesian Inference in Numerical Cognition: A Tutorial Using JASP. Journal of Numerical Cognition, 6(2), 231-259. https://doi.org/10.5964/jnc.v6i2.288
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