Publications

Ly, A., Raj, A., Etz, A., Marsman, M., & Wagenmakers, E.-J. (in press). Bayesian reanalyses from summary statistics: A guide for academic consumers. Advances in Methods and Practices in Psychological Science.

Ly, A., Etz, A., Marsman, M., & Wagenmakers, E.-J. (in press). Replication Bayes factors from evidence updating. Behavior Research Methods.

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., van Ravenzwaaij, D., Vandekerckhove, J., Visser, I., Voss, A., White, C. N., Wiecki, T. V., Rieskamp, J., & Donkin, C. (in press). The quality of response time data inference: A blinded, collaborative approach to the validity of cognitive models. Psychonomic Bulletin & Review.

Heshmati, S., Oravecz, Z., Pressman, S., Batchelder, W. H., Muth, C., & Vandekerckhove, J. (in press). What does it mean to feel loved? Cultural agreement and individual differences. Journal of Social and Personal Relationships.

Zwaan, R. A., Etz, A., Lucas, R. E., & Donnellan, M. B. (2018). Making replication mainstream. Behavioral and Brain Sciences, 41, e120.

Zwaan, R. A., Etz, A., Lucas, R. E., & Donnellan, M. B. (2018). Improving social and behavioral science by making replication mainstream: A response to commentaries. Behavioral and Brain Sciences, 41, e157.

Etz, A., Gronau, Q., 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, 219-234.

Etz, A. (2018). Introduction to the concept of likelihood and its applications. Advances in Methods and Practices in Psychological Science, 1, 60-69.

Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Selker, R., Gronau, Q., Dropmann, D., Boutin, B., Meerhol, F., Knight, P., Raj, A., van Kesteren, E. J., van Doorn, J., Smira, M., Epskamp, S., Etz, A., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian Inference for Psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25, 58-76.

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, 281–295.

Vandekerckhove, J., Rouder, J. N., & Kruschke, J. (2018). Editorial: Bayesian methods for advancing psychological science. Psychonomic Bulletin & Review, 25, 1–4.

Baribault, B., Donkin, C., Little, D. R., Trueblood, J. S., Oravecz, Z., van Ravenzwaaij, D., White, C. N., de Boeck, P., & Vandekerckhove, J. (2018). Metastudies for robust tests of theory. Proceedings of the National Academy of Sciences, 115, 2607–2612.

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

Matzke, D., Boehm, U., & Vandekerckhove, J. (2018). Bayesian Inference in Psychology, Part III: Bayesian parameter estimation in nonstandard models. Psychonomic Bulletin & Review, 25, 77–101.

Etz, A., & Vandekerckhove, J. (2018). Introduction to Bayesian inference for psychology. Psychonomic Bulletin & Review, 25, 5–34.

Okada, K., Vandekerckhove, J., & Lee, M. D. (2018). Modeling when people quit: Bayesian censored geometric models with hierarchical and latent-mixture extensions. Behavior Research Methods, 50, 406–415.

Bapat, A. N., Shafer-Skelton, A., Kupitz, C. N., & Golomb, J. D. (2017). Binding object features to locations: Does the "spatial congruency bias" update with object movement? Attention, Perception, & Psychophysics, 79, 1682-1694.

Shafer-Skelton, A., Kupitz, C. N., & Golomb, J. D. (2017). Object-location binding across a saccade: A retinotopic spatial congruency bias. Attention, Perception, & Psychophysics, 79, 765-781.

Guan, M., & Lee, M. D. (2017). The effects of goals and evironments on human performance in optimal stopping problems. Decision.

Lakens, D., & Etz, A. (2017). Too true to be bad: When sets of studies with significant and non-significant findings are probably true. Social Psychological and Personality Science, 8, 875-881.

Etz, A., & Wagenmakers, E.-J. (2017). J. B. S. Haldane's contribution to the Bayes factor hypothesis test. Statistical Science.

Dutilh, G., Vandekerckhove, J., Ly, A., Matzke, D., Pedroni, A., Frey, R., Rieskamp, J., & Wagenmakers, E.-J. (2017). A test of the diffusion model explanation for the Worst Performance Rule using preregistration and blinding. Attention, Perception, and Performance, 79, 713–725.

van Ravenzwaaij, D., Donkin, C., & Vandekerckhove, J. (2017). The EZ diffusion model provides a powerful test of simple empirical effects. Psychonomic Bulletin & Review, 24, 547–556.

Lucio, P. S., Salum, G. A., Rohde, L. A. P., Gadelha, A., Swardfager, W., Vandekerckhove, J., Pan, P. M., Polanczyk, G. V., do Rosario, M. C., Jackowski, A. P., Mari, J. d. J., & Cogo-Moreira, H. (2017). Poor stimulus discriminability as a common neuropsychological deficit between ADHD and reading ability in young children: a moderated mediation model. Psychological Medicine, 47, 255–266.

Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2017). How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters. Journal of Mathematical Psychology, 76, 117–130.

Nunez, M. D., Nunez, P. L, & Srinivasan, R. (2016). Electroencephalography (EEG): neurophysics, experimental methods, and signal processing. Handbook of Neuroimaging Data Analysis, 175-197.

Holcombe, A. O., Brown, N. J., Goodbourn, P. T., Etz, A., & Geukes, S. (2016). Does sadness impair color perception? Flawed evidence and faulty methods. F1000Research.

Vandekerckhove, J., & Wagenmakers, E.-J. (2016). C. S. Peirce on the Crisis of Confidence and the "No More Bets" Heuristic. The Winnower, 4843.

Oravecz, Z., Muth, C., & Vandekerckhove, J. (2016). Do people agree on what makes one feel loved? A cognitive psychometric approach to the consensus on felt love. PLoS ONE, 11, e0152803.

Etz, A., & Vandekerckhove, J. (2016). A Bayesian perspective on the Reproducibility Project: Psychology. PLoS ONE, 11, e0149794.

Oravecz, Z., Tuerlinckx, F., & Vandekerckhove, J. (2016). Bayesian data analysis with the bivariate hierarchical Ornstein-Uhlenbeck process model. Multivariate Behavioral Research, 51, 106–119.

Guan, M., & Vandekerckhove, J. (2016). A Bayesian approach to mitigation of publication bias. Psychonomic Bulletin & Review, 23, 74–86.

Oravecz, Z., Huentelman, M., & Vandekerckhove, J. (2016). Sequential Bayesian updating for Big Data. Big Data in Cognitive Science: From Methods to Insights, 13–33.

Subiaul, F., Krajkowski, E., Price, E., & Etz, A. (2015). Imitation by combination: Preschool age children evidence summative imitation in a novel problem-solving task. Frontiers in Psychology, 6.

Van Elk, M., Matzke, D., Gronau, Q., Guan, M., Vandekerckhove, J., & Wagenmakers, E.-J. (2015). Meta-analyses are no substitute for registered replications: a skeptical perspective on religious priming. Frontiers in Psychology, 6, 1365.

Kupitz, C. N., Buschkuehl, M., Jaeggi, S. M., Jonides, J., Shah, P., & Vandekerckhove, J. (2015). A diffusion model account of the transfer-of-training effect. Proceedings of the 37th Annual Conference of the Cognitive Science Society.

Guan, M., Lee, M. D., & Vandekerckhove, J. (2015). A hierarchical cognitive threshold model of human decision making on different length optimal stopping problems. Proceedings of the 37th Annual Conference of the Cognitive Science Society.

Mistry, P. K, Trueblood, J. S., Vandekerckhove, J., & Pothos, E. M. (2015). A latent-mixture quantum probability model of causal reasoning within a Bayesian inference framework. Proceedings of the 37th Annual Conference of the Cognitive Science Society.

Nunez, M. D., Srinivasan, R., & Vandekerckhove, J. (2015). Individual differences in attention influence perceptual decision making. Frontiers in Psychology, 6, 18.

Vandekerckhove, J., Matzke, D., & Wagenmakers, E.-J. (2015). Model comparison and the principle of parsimony. Oxford Handbook of Computational and Mathematical Psychology, 300–317.

Guan, M., Lee, M. D., & Silva, A. E. (2014). Threshold models of human decision making on optimal stopping problems in different environments. Proceedings of the 36th Annual Conference of the Cognitive Science Society.

Zhang, S., Lee, M. D., Vandekerckhove, J., Maris, G., & Wagenmakers, E.-J. (2014). Time-varying boundaries for diffusion models of decision making and response time. Frontiers in Psychology, 5, 1364.

Lee, M. D., Newell, B., & Vandekerckhove, J. (2014). Modeling the adaptation of search termination in human decision making. Decision, 1, 223–251.

Murphy, P. R., Vandekerckhove, J., & Nieuwenhuis, S. (2014). Pupil-linked arousal determines variability in perceptual decision making. PLOS Computational Biology, 10, e1003854.

Vandekerckhove, J. (2014). A cognitive latent variable model for the simultaneous analysis of behavioral and personality data. Journal of Mathematical Psychology, 60, 58–71.

Wiech, K., Vandekerckhove, J., Zaman, J., Tuerlinckx, F., Vlaeyen, J. W. S., & Tracey, I. (2014). Influence of prior information on pain involves biased perceptual decision-making. Current Biology, 24, R679–R681.

Wabersich, D., & Vandekerckhove, J. (2014). The RWiener package: an R package providing distribution functions for the Wiener diffusion model. The R Journal, 6, 49–56.

Oravecz, Z., Vandekerckhove, J., & Batchelder, W. H. (2014). Bayesian Cultural Consensus Theory. Field Methods, 26, 207–222.

Salum, G. A., Sergeant, J. A., Sonuga-Barke, E., Vandekerckhove, J., Gadelha, A., Pan, P. M., Moriyama, T. S., Graeff-Martins, A. S., Gomes de Alvarenga, P., do Rosario, M. C., Manfro, G. G., Polanczyk, G. V., & Rohde, L. A. P. (2014). Mechanisms underpinning inattention and hyperactivity: neurocognitive support for ADHD dimensionality. Psychological Medicine, 44, 3189–3201.

Wabersich, D., & Vandekerckhove, J. (2014). Extending JAGS: A tutorial on adding custom distributions to JAGS (with a diffusion model example) Behavior Research Methods, 46, 15-28.

Salum, G. A., Sergeant, J. A., Sonuga-Barke, E., Vandekerckhove, J., Gadelha, A., Pan, P. M., Moriyama, T. S., Graeff-Martins, A. S., Gomes de Alvarenga, P., do Rosario, M. C., Manfro, G. G., Polanczyk, G. V., & Rohde, L. A. P. (2014). Specificity of basic information processing and inhibitory control in attention deficit/hyperactivity disorder. Psychological Medicine, 44, 617–631.

Chubb, C., Dickson, C. A., Dean, T., Fagan, C., Mann, D. S., Wright, C. E., Guan, M., Silva, A. E., Gregersen, P. K., & Kowalsky, E. (2013). Bimodal distribution of performance in discriminating major/minor modes. The Journal of the Acoustical Society of America, 134, 3067-3078.

Vandekerckhove, J., Guan, M., & Styrcula, S. (2013). The consistency test may be too weak to be useful: Its systematic application would not improve effect size estimation in meta-analyses. Journal of Mathematical Psychology, 57, 170–173.

Pe, M., Vandekerckhove, J., & Kuppens, P. (2013). A diffusion model account of the relationship between the emotional flanker task and depression and rumination. Emotion, 13, 739–747.

Dutilh, G., Forstmann, B. U., Vandekerckhove, J., & Wagenmakers, E.-J. (2013). A diffusion model account of age differences in posterror slowing. Psychology and Aging, 28, 64–76.

Dutilh, G., Vandekerckhove, J., Forstmann, B. U., Keuleers, E., Brysbaert, M., & Wagenmakers, E.-J. (2012). Testing theories of post-error slowing. Attention, Perception, & Psychophysics, 7, 454–465.

Oravecz, Z., Tuerlinckx, F., & Vandekerckhove, J. (2011). A hierarchical latent stochastic differential equation model for affective dynamics. Psychological Methods, 16, 468–490.

Vandekerckhove, J., Tuerlinckx, F., & Lee, M. D. (2011). Hierarchical diffusion models for two-choice response times. Psychological Methods, 16, 44–62.

Vandekerckhove, J., Verheyen, S., & Tuerlinckx, F. (2010). A crossed random effects diffusion model for speeded semantic categorization data. Acta Psychologica, 133, 269–282.

Wetzels, R., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E.-J. (2010). Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task. Journal of Mathematical Psychology, 54, 14–27.

Dutilh, G., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E.-J. (2009). A diffusion model decomposition of the practice effect. Psychonomic Bulletin & Review, 16, 1026–1036.

Oravecz, Z., Tuerlinckx, F., & Vandekerckhove, J. (2009). A hierarchical Ornstein-Uhlenbeck model for continuous repeated measurement data. Psychometrika, 74, 395–418.

Panis, S., De Winter, J., Vandekerckhove, J., & Wagemans, J. (2008). Identification of everyday objects on the basis of fragmented versions of outlines. Perception, 37, 271–289.

Vandekerckhove, J., & Tuerlinckx, F. (2008). Diffusion Model Analysis with MATLAB: A DMAT Primer. Behavior Research Methods, 40, 61–72.

Vandekerckhove, J., Tuerlinckx, F., & Lee, M. D. (2008). A Bayesian approach to diffusion process models of decision-making. Proceedings of the 30th Annual Conference of the Cognitive Science Society, 1429–1434.

Spruyt, A., Hermans, D., De Houwer, J., Vandekerckhove, J., & Eelen, P. (2007). On the predictive validity of indirect attitude measures: Prediction of consumer choice behavior on the basis of affective priming in the picture--picture naming task. Journal of Experimental Social Psychology, 43, 599–610.

Vandekerckhove, J., Panis, S., & Wagemans, J. (2007). The concavity effect is a compound of local and global effects. Perception & Psychophysics, 69, 1253–1260.

Vandekerckhove, J., & Tuerlinckx, F. (2007). Fitting the Ratcliff diffusion model to experimental data. Psychonomic Bulletin & Review, 14, 1011–1026.