Joachim Vandekerckhove

Principal Investigator and Pursuer of Lofty Undertakings Personal website: Email: Curriculum vitae

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

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.

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

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

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

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

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.

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.

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.

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.

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.

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). Mechanisms underpinning inattention and hyperactivity: neurocognitive support for ADHD dimensionality. Psychological Medicine, 44, 3189–3201.

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

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.

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.

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

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

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

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.

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.

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.

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.

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.

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

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

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.

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

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

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

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.

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

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

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