Publications

Aczel, B., Szaszi, B., Nilsonne, G., van den Akker, O.R., Albers, C.J., van Assen, M.A.L.M., Bastiaansen, J. A., Benjamin, D., Boehm, U., …, Matzke, D., …, & Wagenmakers, E.-J. (2021). Consensus-based guidance for conducting and reporting multi-analyst studies. eLife,10:e7218.

Rouder, J. N., & Haaf, J. M. (2021). Are There Reliable Qualitative Individual Difference in Cognition? Journal of Cognition, 4(1), 46.

Tierney, W., Hardy, J. H., III., Ebersole, C., Viganola, D., Clemente, E., Gordon, M., Hoogeveen, S., Haaf, J., Dreber, A.A., Johannesson, M., Pfeiffer, T., Chapman, H., Gantman, A., Vanaman, M., DeMarree, K., Igou, E., Wylie, J., Storbeck J., Andreychik, M.R., McPhetres, J., Vaughn, L.A., Culture and Work Morality Forecasting Collaboration, & Uhlmann, E. L. (2021). A creative destruction approach to replication: Implicit work and sex morality across cultures. Journal of Experimental Social Psychology, 93, 104060.

Haaf, J. M., Rhodes, S., Naveh-Benjamin, M., Sun, T. K., Snyder, H. K., & Rouder, J. N. (2021). Revisiting the Remember-Know Task: Replications of Gardiner and Java (1990). Memory & Cognition, 49, 46-66. [OSF project]

van den Bergh, D., Haaf, J. M., Ly, A., Rouder, J. N., & Wagenmakers, E. J. (2021). A cautionary note on estimating effect size. Advances in Methods and Practices in Psychological Science, 4(1), 1-15.

van Doorn, J., van den Bergh, D., Dablander, F., van Dongen, N., Derks, K., Evans, N., Gronau, Q., Haaf, J. M., Kunisato, Y., Ly, A., Marsman, M., Sarafoglou, A., Stefan, A., & Wagenmakers, E. (2021). Strong Public Claims May Not Reflect Researchers’ Private Convictions. Significance, 18, 44-45.

Manning, C., Wagenmakers, E.-J., Norcia, A. M., Serif, G., & Boehm, U. (2021). Perceptual decisionmaking
in children: Age-related differences and EEG correlates. Computational Brain & Behavior, 4, 53-69.

Retzler, C., Boehm, U., Jing, C., Cochrane, A., & Manning, C. (2021). Prior information use and
response caution in perceptual decision-making: No evidence for a relationship with autistic-like traits.
Quarterly Journal of Experimental Psychology, 74(11): 1953–1965.

van Berkel, N., Dennis, S., Zyphur, M., Li, J., Heathcote, A. & Kostakos, V. (2021). Modeling interaction as a complex system. Human-Computer Interaction, 36, 279-305.

Parker, S., Heathcote, A., & Finkbeiner, M. (2021). Establishing the separable contributions of spatial attention and saccade preparation across tasks with varying acuity demands. Journal of Experimental Psychology: Human Perception and Performance, 47(2), 172–188.

Miletić, S., Boag, R. J., Trutti, A. C., Stevenson, N., Forstmann, B. U., & Heathcote, A. (2021). A new model of decision processing in instrumental learning tasks. ELife, 10, e63055.

Trueblood, J. S., Heathcote, A., Evans, N. J., & Holmes, W. R. (2021). Urgency, leakage, and the relative nature of information processing in decision-making. Psychological Review, 128(1), 160–186.

Hawkins, G. E., & Heathcote, A. (2021). Racing against the clock: Evidence-based versus time-based decisions. Psychological Review, 128(2), 222–263. [Supplementary Materials]

Reynolds, A., Garton, R., Kvam, P., Sauer, J., Osth, A. F., & Heathcote, A. (2021). A dynamic model of deciding not to choose. Journal of Experimental Psychology: General, 150(1), 42–66. [Supplementary Materials]

Strickland, L., Heathcote, A., Bowden, V., Boag, R., Wilson, M. D., Khan, S. & Loft, S. (2021). Inhibitory cognitive control allows automated advice to improve accuracy while minimizing misuse. Psychological Science, 32,1768-1781.

Shiffrin, R. M., Matzke, D., Crystal, J. D., Wagenmakers, E.-J., Chandramouli, S. H., Vandekerckhove, J., Zorzi, M., Morey, R. D., & Murphy, M. C. (2021). Extraordinary claims, extraordinary evidence? A discussion. Learning & Behavior, 49, 265-275.

Tanis, C. C., Leach, N. M., Geiger, S. J., Nauta, F. H., Dablander, F., Harreveld, F. van, … Blanken, T. F. (2021). Smart Distance Lab’s art fair, experimental data on social distancing during the COVID-19 pandemic. Scientific Data, 8, 179.

Blanken, T. F., Tanis, C. C., Nauta, F. H., Dablander, F., Zijlstra B., Bouten, R. R. M., Oostvogel, Q. H., Boersma, M. J., Van der Steenhoven, F., Van Harreveld, F., De Wit, S., & Borsboom, D. (2021). Promoting physical distancing during COVID-19: a systematic approach to compare behavioral interventions. Scientific Reports, 11(1), 1-8.

Tran, N.-H., van Maanen, L., Heathcote, A., & Matzke, D. (2021). Systematic quantitative parameter reviews in cognitive modeling: Towards robust and cumulative models of psychological processes. Frontiers in Psychology: Quantitative Psychology and Measurement, 11:608287.

van Doorn, J., van den Bergh, D., Boehm, U., Dablander, F., Derks, K., Draws, T., Evans, N.J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharsky, S., Ly, A., Marsman, M., Matzke, D., Raj, A.K.N., Sarafoglou, A., Stefan, A., Voelkel, A.G., & Wagenmakers, E.-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28, 813–826.

Boehm, U., Matzke, D., Gretton, M., Castro, S., Cooper, J., Skinner,  M., Strayer, D., & Heathcote, A. (2021). Real-time prediction of fluctuations in cognitive workload. Cognitive Research: Principles and Implications, 6:30. 

Damaso, K.A.M., Castro, S.C., Todd, J., Strayer, D.L., Provost, A., Matzke, D., & Heathcote, A.J. (2022). A cognitive model of response omissions in distraction paradigms. Memory & Cognition, 50, 962-978. [Supplementary Materials]

Bergh, D. van den, Clyde, M. A., Komarlu Narendra Gupta, A. R. K. N., de Jong, T., Gronau, Q. F., Marsman, M., Ly, A., & Wagenmakers, E.-J. (2021). A tutorial on Bayesian multi-model linear regression with BAS and JASP. Behavior Research Methods.

Hulme, O. J., Wagenmakers, E.-J., Damkier, P., Madelung, C. F., Siebner, H. R., Helweg-Larsen, J., Gronau, Q. F., Benfield, T. L., & Madsen, K. H. (2021). A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19. PLOS ONE, 16(2), e0245048.

Snyder, H. K., Rafferty, S. M., Haaf, J. M., & Rouder, J. N. (2019). Common or Distinct Attention Mechanisms for Contrast and Assimilation. Attention, Perception, & Psychophysics, 81(6). 1944-1950.

Rouder, J. N., Haaf, J. M., & Snyder, H. K. (2019). Minimizing Mistakes In Psychological Science. Advances in Methods and Practices in Psychological Science, 2(1), 3-11.

Rouder, J. N., Haaf, J. M., Davis-Stober, C., & Hilgard, J. (2019). Beyond overall effects: A Bayesian approach to finding constraints across a collection of studies in meta-analysis. Psychological Methods, 24(5), 606–621.

Rouder, J. N., & Haaf, J. M. (2019). A Psychometrics of Individual Differences in Experimental Tasks. Psychonomic Bulletin and Review, 26(2), 452-467.

Haaf, J. M., & Rouder, J. N. (2019). Some do and some don’t? Accounting for variability of individual difference structures. Psychonomic Bulletin and Review, 26(3), 772-789.

Haaf, J. M., Ly, A., & Wagenmakers, E.-J. (2019). Retire significance, but still test hypotheses. Nature, 567, 461.

Aust, F., Haaf, J. M., & Stahl, C. (2019). A memory-based judgment account of expectancy-liking dissociations in evaluative conditioning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(3), 417-439. [OSF project]

Heathcote, A., Holloway, E., & Sauer, J. (2019). Confidence and varieties of bias. Journal of Mathematical Psychology, 90, 31–46.

Dunn, J. C., Heathcote, A., & Kalish, M. (2019). Special issue on state-trace analysis. Journal of Mathematical Psychology, 90, 1–2. [Full Issue]

Lin, Y.-S., Heathcote, A., & Holmes, W. R. (2019). Parallel probability density approximation. Behavior Research Methods, 51(6), 2777–2799. [R package]

Garton, R., Reynolds, A., Hinder, M. R., & Heathcote, A. (2019). Equally flexible and optimal response bias in older compared to younger adults. Psychology and Aging, 34(6), 821–835. [Supplementary Materials]

Boag, R. J., Strickland, L., Heathcote, A., Neal, A., & Loft, S. (2019). Cognitive control and capacity for prospective memory in complex dynamic environments. Journal of Experimental Psychology. General, 148(12), 2181–2206.

Bird, L., Gretton, M., Cockerell, R., & Heathcote, A. (2019). The cognitive load of narrative lies. Applied Cognitive Psychology, 33(5), 936–942.

Hawkins, G. E., Mittner, M., Forstmann, B. U., & Heathcote, A. (2019). Modeling distracted performance. Cognitive Psychology, 112, 48–80. [Supplementary Material & Code]

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. [Supplementary Materials]

Strickland, L., Elliott, D., Wilson, M. D., Loft, S., Neal, A., & Heathcote, A. (2019). Prospective memory in the red zone: Cognitive control and capacity sharing in a complex, multi-stimulus task. Journal of Experimental Psychology: Applied, 25(4), 695–715.

Palada, H., Neal, A., Strayer, D., Ballard, T., & Heathcote, A. (2019). Using response time modeling to understand the sources of dual-task interference in a dynamic environment. Journal of Experimental Psychology: Human Perception and Performance, 45(10), 1331–1345.

Starns, J. J., Cataldo, A. M., Rotello, C. M., Annis, J., Aschenbrenner, A., Bröder, A., Cox, G., Criss, A., Curl, R. A., Dobbins, I. G., Dunn, J., Enam, T., Evans, N. J., Farrell, S., Fraundorf, S. H., Gronlund, S. D., Heathcote, A., Heck, D. W., Hicks, J. L., … Wilson, J. (2019). Assessing theoretical conclusions with blinded inference to investigate a potential inference crisis. Advances in Methods and Practices in Psychological Science, 2(4), 335–349.

Weigard, A., Heathcote, A., & Sripada, C. (2019). Modeling the effects of methylphenidate on interference and evidence accumulation processes using the conflict linear ballistic accumulator. Psychopharmacology, 236(8), 2501–2512. [Data & Code]

Boag, R. J., Strickland, L., Loft, S., & Heathcote, A. (2019). Strategic attention and decision control support prospective memory in a complex dual-task environment. Cognition, 191, 103974.

Heathcote, A. (2019). What do the rules for the wrong game tell us about how to play the right game? Computational Brain & Behavior, 2(3), 187–189.

Osth, A. F., Dunn, J. C., Heathcote, A., & Ratcliff, R. (2019). Two processes are not necessary to understand memory deficits. Behavioral and Brain Sciences, 42.

Gronau, Q. F., Raj K. N., A., & Wagenmakers, E.-J. (2019). abtest: Bayesian A/B testing. R package
version 0.2.0.

Strickland, L., Loft, S., & Heathcote, A. (2019). Evidence accumulation modeling of event-based prospective memory. In J. Rummel & M.A. McDaniel (Eds.), Current issues in memory: Prospective memory (pp. 78-94). Taylor & Francis.

Schubert, A. L., Nunez, M. D., Hagemann, D., & Vandekerckhove, J. (2019). Individual differences in cortical processing speed predict cognitive abilities: A model-based cognitive neuroscience account. Computational Brain & Behavior, 2(2), 64-84.

Nunez, P. L., Nunez, M. D., & Srinivasan, R. (2019). Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review. Brain Topography, 1-22.

Nunez, M. D., Gosai, A., Vandekerckhove, J., & Srinivasan, R. (2019). The latency of a visual evoked potential tracks the onset of decision making. NeuroImage, 197, 93-108.

Skippen, P., Matzke, D., Heathcote, A., Fulham, W.R., Michie, P., Karayanidis, F. (2019). Reliability of triggering inhibitory process is a better predictor of impulsivity than SSRT. Acta Psychologica, 192, 104-117.

Gronau, Q.F., Wagenmakers, E.-J., Heck, D.W., & Matzke, D. (2019). A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling. Psychometrika, 84, 261-284.

Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, J., Ly, A., Gronau, Q. F., …, Matzke, D., …, & Wagenmakers, E.-J. (2019). JASP- Graphical statistical software for common statistical designs. Journal of Statistical Software, 88, 1-17.

Matzke, D., Curley, S., Gong, C.Q., & Heathcote, A. (2019). Inhibiting responses to difficult choices. Journal of Experimental Psychology: General, 148, 124-142. [Supplementary Materials]

Heathcote, A., Lin, Y., Reynolds, A., Strickland, L., Gretton, M., & Matzke, D. (2019). Dynamic models of choice. Behavior Research Methods, 51, 961-985. [Software]

Castro, S., Strayer, D., Matzke, D., & Heathcote, A. (2019). Cognitive workload measurement and modeling under divided attention. Journal of Experimental Psychology: Human Perception and Performance, 45, 826-839.

Stephens, R.G., Matzke, D., & Hayes, B.K. (2019). Disappearing dissociations in experimental psychology: Using state-trace analysis to test for multiple processes. Journal of Mathematical Psychology, 90, 3–22.

Weigard, A., Heathcote, A., Matzke, D., & Huang-Pollock, C. (2019). Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in attention deficit/hyperactivity disorder. Clinical Psychological Science, 7, 856-872. [Code]

Verbruggen, F., Aron, A.R., Band, G.P.H., Beste, C., Bissett, P.G., Brockett, A.T., …, Heathcote, A., …, Matzke, D., …, Boehler, C.N. (2019). A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. eLIFE, 8, e46323. [Supplementary Materials]

Lee, M., Criss, A.H., Devezer, B., Donkin, C., Etz, A., Leite,F., Matzke, D., …, Vandekerckhove, J. (2019). Robust modeling in cognitive science. Computational Brain & Behavior, 2, 141–153.

Vandekerckhove, J., White, C.N., Trueblood, J.S., Rouder, J.N., Matzke, D., Leite, F.P., …, Lee., M.D. (2019). Robustness and diversity in cognitive modeling. Computational Brain & Behavior, 2, 271–276.

Marsman, M., Tanis, C. C., Bechger, T. M., & Waldorp, L. J. Network Psychometrics in Educational Practice. In B. P. Veldkamp & C. Sluijter (Eds.). Theoretical and Practical Advances in Computer-based Educational Measurement (pp. 93–120). Cham: Springer International Publishing

Gronau, Q. F., & Wagenmakers, E.-J. (2019). Limitations of Bayesian leave-one-out cross-validation for model selection. Computational Brain & Behavior, 2(1), 1–11.

Gronau, Q. F., & Wagenmakers, E.-J. (2019). Rejoinder: More limitations of Bayesian leave-one-out cross-validation. Computational Brain & Behavior, 2(1), 35–47.

Boffo, M., Zerhouni, O., Gronau, Q. F., van Beek, R. J. J., Nikolaou, K., Marsman, M., & Wiers, R. W. (2019). Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian meta-analysis of individual participant data. Neuropsychology Review, 29(1), 52–78.

Dongen, N. N. N. van, Doorn, J. B. van, Gronau, Q. F., Ravenzwaaij, D. van, Hoekstra, R., Haucke, M. N., Lakens, D., Hennig, C., Morey, R. D., Homer, S., Gelman, A., Sprenger, J., & Wagenmakers, E.-J. (2019). Multiple perspectives on inference for two simple statistical scenarios. The American Statistician, 73(sup1), 328–339.

Heck, D. W., Overstall, A. M., Gronau, Q. F., & Wagenmakers, E.-J. (2019). Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. Statistics and Computing, 29(4), 631–643.

Stefan, A. M., Gronau, Q. F., Schönbrodt, F. D., & Wagenmakers, E.-J. (2019). A tutorial on Bayes Factor Design Analysis using an informed prior. Behavior Research Methods, 51(3), 1042–1058.

Brown, S., & Heathcote, A. (2003). Averaging learning curves across and within participants. Behavior Research Methods, Instruments, & Computers, 35(1), 11–21.

Brown, S., & Heathcote, A. (2003). QMLE: Fast, robust, and efficient estimation of distribution functions based on quantiles. Behavior Research Methods, Instruments, & Computers, 35(4), 485–492.

Brown, S., & Heathcote, A. (2003). Bias in exponential and power function fits due to noise: Comment on Myung, Kim, and Pitt. Memory & Cognition, 31(4), 656–661.

Heathcote, A. (2003). Item recognition memory and the receiver operating characteristic. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(6), 1210–1230.

Karayanidis, F., Coltheart, M., Michie, P. T., & Murphy, K. (2003). Electrophysiological correlates of anticipatory and poststimulus components of task switching. Psychophysiology, 40(3), 329–348.

Hill, J., Rolfe, I. E., Pearson, S.-A., & Heathcote, A. (1998). Do junior doctors feel they are prepared for hospital practice? A study of graduates from traditional and non-traditional medical schools. Medical Education, 32(1), 19–24.