Publications

Rouder, J. N., Haaf, J. M., & Aust, F. (2018). From theories to models to predictions: A Bayesian model comparison approach. Communication Monographs, 85(1), 41-56.

Rouder, J., & Haaf, J. (2018). Power, Dominance, and Constraint: A Note on the Appeal of Different Design Traditions. Advances in Methods and Practice in Psychological Science, 1(1), 19-26. [GitHub repository]

Rouder, J. N., Haaf, J. M., & Vandekerckhove, J. (2018). Bayesian Inference in Psychology, Part IV: Parameter estimation and Bayes factors. Psychonomic Bulletin and Review, 25(1), 102-113.

Heycke, T., Gehrmann, S. M., Haaf, J., & Stahl, C. (2018). Of two minds or one? A registered replication of Rydell et al. (2006). Emotion and Cognition, 32(8), 1708-1727. [OSF project]

Etz, A., Haaf, J. M., Rouder, J. N., & Vandekerckhove, J. (2018). Bayesian inference and testing any hypothesis you can specify. Advances in Methods and Practices in Psychological Science, 1(2), 281-295. [OSF project (with app)]

Quinn, R. K., James, M. H., Hawkins, G. E., Brown, A. L., Heathcote, A., Smith, D. W., Cairns, M. J., & Dayas, C. V. (2018). Temporally specific miRNA expression patterns in the dorsal and ventral striatum of addiction-prone rats. Addiction Biology, 23(2), 631–642.

Provost, A., Jamadar, S., Heathcote, A., Brown, S. D., & Karayanidis, F. (2018). Intertrial RT variability affects level of target-related interference in cued task switching. Psychophysiology, 55(3), e12971.

Weigard, A., Huang-Pollock, C., Brown, S., & Heathcote, A. (2018). Testing formal predictions of neuroscientific theories of ADHD with a cognitive model-based approach. Journal of Abnormal Psychology, 127(5), 529–539. [Supplementary Materials]

Osth, A. F., Jansson, A., Dennis, S., & Heathcote, A. (2018). Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making. Cognitive Psychology, 104, 106–142. [Data]

Osth, A. F., Fox, J., McKague, M., Heathcote, A., & Dennis, S. (2018). The list strength effect in source memory: Data and a global matching model. Journal of Memory and Language, 103, 91–113. [Supplementary Data Set 1, Data Set 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. [Data]

Strickland, L., Loft, S., Remington, R. W., & Heathcote, A. (2018). Racing to remember: A theory of decision control in event-based prospective memory. Psychological Review, 125(6), 851–887. [Supplementary Material]

Palada, H., Neal, A., Tay, R., & Heathcote, A. (2018). Understanding the causes of adapting, and failing to adapt, to time pressure in a complex multistimulus environment. Journal of Experimental Psychology. Applied, 24(3), 380–399.

Weigard, A., Huang-Pollock, C., Heathcote, A., Hawk, L., & Schlienz, N. J. (2018). A cognitive model-based approach to testing mechanistic explanations for neuropsychological decrements during tobacco abstinence. Psychopharmacology, 235(11), 3115–3124. [Supplementary Materials]

Boehm, U., Steingroever, H., & Wagenmakers, E-J. (2018). Using Bayesian regression to test hypotheses
about relationships between parameters and covariates in cognitive models. Behavior Research Methods,
50 (3), 1248–1269.

Gronau, Q. F. & Singmann, H. (2018). bridgesampling: Bridge sampling for marginal likelihoods
and Bayes Factors. R package version 0.7-2.

Ly, A., Boehm, 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.

Matzke, D., Boehm, U., & Vandekerckhove, J. (2018). Bayesian inference for psychology. Part III: Parameter estimation in nonstandard models. Psychonomic Bulletin & Review, 25, 77-101.

Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, A.J., …,Gronau, Q.F., …, Matzke, D., et al. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25, 58-76.

Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, A.J., Love, J., …, Matzke, D., et al. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25, 35-57.

Sebastian, A., Forstmann, B.U., & Matzke, D. (2018). Towards a model-based cognitive neuroscience of stopping: A neuroimaging perspective. Neuroscience & Biobehavioral Reviews, 90, 130-136.

Matzke, D., Verbruggen, F., & Logan, G. (2018). The stop-signal paradigm. In E.-J. Wagenmakers & J.T. Wixted (Eds.), Stevens’ handbook of experimental psychology and cognitive neuroscience, Volume five: Methodology (4th ed., pp. 383-427). John Wiley & Sons, Inc.

Beek, T.F., Matzke, D., Pinto, Y., Rotteveel, M., Gierholz, A., Verhagen, J., et al. (2018). Incidental haptic sensations may not influence social judgements: A purely confirmatory replication attempt of Study 1 by Ackerman, Noreca, & Bargh (2010). Journal of Articles in Support of the Null Hypothesis, 14, 69-90.

Bridwell, D. A., Cavanagh, J. F., Collins, A. G., Nunez, M. D., Srinivasan, R., Stober, S., & Calhoun, V. D. (2018). Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior. Frontiers in Human Neuroscience, 12, 106.

Boehm, U., Marsman, M., Matzke, D., & Wagenmakers, E.-J. (2018). On the importance of avoiding shortcuts in applying cognitive models to hierarchical data. Behavioral Research Methods, 50, 1614-1631.

Boehm, U., Annis, J., Frank, M.J., Hawkins, G.E., Heathcote, A., Kellen, D., …, Matzke, D., & Wagenmakers, E.-J. (2018). Estimating between-trial variability parameters of the diffusion decision model: Expert advice and recommendations. Journal of Mathematical Psychology, 87, 46-75. [Supplementary Materials & Data]

Derks, K., Burger, J., van Doorn, J., Kossakowski, J.J., Matzke, D., Atticciati, L., et al. (2018). Network models to organize a dispersed literature: A case of misunderstanding analysis of covariance. Journal of European Psychology Students, 9, 48-57.

Nunez, M.D., Horton, C., Deng, s., Winter, W., & Srinivasan, R. (2018) – artscreenEEG: MATLAB repository to perform basic artifact correction on EEG data. MATLAB package version 0.14.2

Charupanit, K., Nunez, M. D., Bernardo, D., Bebin, E. M., Krueger, D. Northrup, H., Sahin, M., Wu, J. Y., & Lopour, B. A. (2018). Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. International Conference of the IEEE Engineering in Medicine and Biological Society. Honolulu, Hawaii. July 2018.

Etz, A., Gronau, Q. F., Dablander, F., Edelsbrunner, P. A., & Baribault, B. (2018). How to become a Bayesian in eight easy steps: An annotated reading list. Psychonomic Bulletin & Review, 25(1), 219–234.

Aczel, B., Palfi, B., Szollosi, A., Kovacs, M., Szaszi, B., Szecsi, P., Zrubka, M., Gronau, Q. F., van den Bergh, D., & Wagenmakers, E.-J. (2018). Quantifying support for the null hypothesis in psychology: An empirical investigation. Advances in Methods and Practices in Psychological Science, 1(3), 357–366.

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.

Gronau, Q. F., & Wagenmakers, E.-J. (2018). Bayesian evidence accumulation in experimental mathematics: A case study of four irrational numbers. Experimental Mathematics, 27(3), 277–286.

Heathcote, A., Popiel, S. J., & Mewhort, D. J. (1991). Analysis of response time distributions: An example using the Stroop task. Psychological Bulletin, 109(2), 340–347.

McNicol, D. & Heathcote, A. (1986).  Representation of order information: An analysis of grouping effects in short-term memory. .Journal of Experimental Psychology: General, 115, 76-95.