Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 60
Number of items: 60
  • Open Access
    Haaf, J. M., Ly, A., & Wagenmakers, E.-J. (2019). Retire significance, but still test hypotheses. Nature, 567(7749), 461. https://doi.org/10.1038/d41586-019-00972-7
  • Open Access
    van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2019). Bayesian estimation of Kendall’s τ using a latent normal approach. Statistics and Probability Letters, 145, 268-272. https://doi.org/10.1016/j.spl.2018.10.004
  • Open Access
    Ly, A., Etz, A., Marsman, M., & Wagenmakers, E.-J. (2019). Replication Bayes factors from evidence updating. Behavior Research Methods, 51(6), 2498–2508. https://doi.org/10.3758/s13428-018-1092-x
  • Open Access
    Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, J., Ly, A., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Wild, A., Knight, P., Rouder, J. N., Morey, R. D., & Wagenmakers, E.-J. (2019). JASP: Graphical statistical software for common statistical designs. Journal of Statistical Software, 88, Article 2. https://doi.org/10.18637/jss.v088.i02
  • Hu, C.-P., Kong, X.-Z., Wagenmakers, E.-J., Ly, A., & Peng, K. (2018). The Bayes factor and its implementation in JASP: A practical primer. Xinli kexue jinzhan, 26(6), 951–965. https://doi.org/10.3724/SP.J.1042.2018.00951
  • Ly, A., Böhm, U., Heathcote, A., Turner, B. M., Forstmann, B., Marsman, M., & Matzke, D. (2018). A flexible and efficient hierarchical Bayesian approach to the exploration of individual differences in cognitive-model-based neuroscience. In A. A. Moustafa (Ed.), Computational Models of Brain and Behavior (pp. 467-480). Wiley Blackwell. https://doi.org/10.1002/9781119159193.ch34
  • Open Access
    Ly, A., Marsman, M., & Wagenmakers, E.-J. (2018). Analytic posteriors for Pearson's correlation coefficient. Statistica Neerlandica, 72(1), 4-13. https://doi.org/10.1111/stan.12111
  • Open Access
    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. https://doi.org/10.1177/2515245918779348
  • Open Access
    Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35-57. https://doi.org/10.3758/s13423-017-1343-3
  • Open Access
    Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Selker, R., Gronau, Q. F., Dropmann, D., Boutin, B., Meerhoff, F., Knight, P., Raj, A., van Kesteren, E.-J., van Doorn, J., Šmíra, M., Epskamp, S., Etz, A., Matzke, D., ... Morey, R. D. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25(1), 58-76. https://doi.org/10.3758/s13423-017-1323-7
Page 4 of 6