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Results: 68
Number of items: 68
  • Open Access
    Hawkins, G. E., Mittner, M., Forstmann, B. U., & Heathcote, A. (2019). Modeling distracted performance. Cognitive Psychology, 112, 48-80. https://doi.org/10.1016/j.cogpsych.2019.05.002
  • Open Access
    Dutilh, G., Annis, J., Brown, S. D., Cassey, P., Evans, N. J., Grasman, R. P. P. P., Hawkins, G. E., Heathcote, A., Holmes, W. R., Krypotos, A.-M., Kupitz, C. N., Leite, F. P., Lerche, V., Lin, Y.-S., Logan, G. D., Palmeri, T. J., Starns, J. J., Trueblood, J. S., van Maanen, L., ... Donkin, C. (2019). The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models. Psychonomic Bulletin & Review, 26(4), 1051-1069. https://doi.org/10.3758/s13423-017-1417-2
  • Evans, N. J., Brown, S. D., Mewhort, D. J. K., & Heathcote, A. (2018). Refining the Law of Practice. Psychological Review, 125(4), 592-605. https://doi.org/10.1037/rev0000105
  • 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
    Boehm, U., Annis, J., Frank, M. J., Hawkins, G. E., Heathcote, A., Kellen, D., Krypotos, A.-M., Lerche, V., Logan, G. D., Palmeri, T. J., van Ravenzwaaij, D., Servant, M., Singmann, H., Starns, J. J., Voss, A., Wiecki, T. V., Matzke, D., & Wagenmakers, E.-J. (2018). Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations. Journal of Mathematical Psychology, 87, 46-75. https://doi.org/10.1016/j.jmp.2018.09.004
  • Hawkins, G. E., Mittner, M., Forstmann, B. U., & Heathcote, A. (2017). On the efficiency of neurally-informed cognitive models to identify latent cognitive states. Journal of Mathematical Psychology, 76(Part B), 142-155. https://doi.org/10.1016/j.jmp.2016.06.007
  • Open Access
    Matzke, D., Love, J., & Heathcote, A. (2017). A Bayesian approach for estimating the probability of trigger failures in the stop-signal paradigm. Behavior Research Methods, 49(1), 267-281. https://doi.org/10.3758/s13428-015-0695-8
  • Open Access
    Matzke, D., Hughes, M., Badcock, J. C., Michie, P., & Heathcote, A. (2017). Failures of cognitive control or attention? The case of stop-signal deficits in schizophrenia. Attention, Perception & Psychophysics, 79(4), 1078-1086. https://doi.org/10.3758/s13414-017-1287-8
  • Open Access
    van Maanen, L., Forstmann, B. U., Keuken, M. C., Wagenmakers, E.-J., & Heathcote, A. (2016). The impact of MRI scanner environment on perceptual decision-making. Behavior Research Methods, 48(1), 184-200. https://doi.org/10.3758/s13428-015-0563-6
  • Terry, A., Marley, A. A. J., Barnwal, A., Wagenmakers, E. J., Heathcote, A., & Brown, S. D. (2015). Generalising the drift rate distribution for linear ballistic accumulators. Journal of Mathematical Psychology, 68-69, 49-58. https://doi.org/10.1016/j.jmp.2015.09.002
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