Publications (funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - GRK 2277 "Statistical Modeling in Psychology")


Peer-reviewed journal articles

in press

Erdfelder, E. & Heck, D. W. (in press). Detecting evidential value and p-hacking with the p-curve tool: A word of caution. Zeitschrift für Psychologie.

Heck, D. W., & Erdfelder, E. (in press). Benefits of Response Time-Extended Multinomial Processing Tree Models: A Reply to Starns (2018). Psychonomic Bulletin & Review.

Heck, D. W., & Erdfelder, E. (in press). Maximizing the expected information gain of cognitive modeling via design optimization. Computational Brain & Behavior.

Heck, D. W., Thielmann, I., Klein, S. A., & Hilbig, B. E. (in press). On the limited generality of air pollution and anxiety as causal determinants of unethical behavior: Commentary on Lu, Lee, Gino, & Galinsky (2018). Psychological Science.

Schild, C., Heck, D. W., Ścigała, K., & Zettler, I. (in press). Revisiting REVISE: (Re)Testing unique and combined effects of REminding, VIsibility, and SElf-engagement manipulations on cheating behavior. Journal of Economic Psychology. doi:10.1016/j.joep.2019.04.001

Schnuerch, M. & Erdfelder, E. (in press). Controlling Decision Errors with Minimal Costs: The Sequential Probability Ratio t-Test. Psychological Methods.

Ścigała, K., Schild, C., Heck, D. W., & Zettler, I. (in press). Who deals with the devil: Interdependence, personality, and corrupted collaboration. Social Psychological and Personality Science. doi:10.1177/1948550618813419

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., Huff, M. J., Kellen, D., Key, K. N., Kilic, A., Klauer, K. C., Kraemer, K. R., Leite, F. P., Lloyd, M. E., Malejka, S., Mason, A., McAdoo, R. M., McDonough, I. M., Michael, R. B., Mickes, L., Mizrak, E., Morgan, D. P., Mueller, S. T., Osth, A., Reynolds, A., Seale-Carlisle, T. M., Singmann, H., Sloane, J. F., Smith, A. M., Tillman, G., van Ravenzwaaij, D., Weidemann, C. T., Wells, G. L., White, C. N., & Wilson, J. (in press). Assessing theoretical conclusions with blinded inference to investigate a potential inference crisis. Advances in Methods and Practices in Psychological Science.

Voss A., Mertens, U., & Radev, S. T. (in press). Learning the likelihood: using deep inference  for the estimation of diffusion-model and lévy flight parameters.

2019

Arnold, N. R., Heck, D. W., Bröder, A., Meiser, T., & Boywitt, D. C. (2019). Testing hypotheses about binding in context memory with a hierarchical multinomial modeling approach: A preregistered study. Experimental Psychology, 66, 239-251. doi:10.1027/1618-3169/a000442

Brandt, M., Zaiser, A.-K., & Schnuerch, M. (2019). Homogeneity of item material boosts the list length effect in recognition memory: A global matching perspective. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(5), 834-850. doi: 10.1037/xlm0000594

Gronau, Q. F., Wagenmakers, E., 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. doi:10.1007/s11336-018-9648-3

Heck, D. W. (2019). A caveat on the Savage-Dickey density ratio: The case of computing Bayes factors for regression parameters. British Journal of Mathematical and Statistical Psychology, 72, 316-333. doi:10.1111/bmsp.12150

Heck, D. W. (2019). Accounting for estimation uncertainty and shrinkage in Bayesian within-subject intervals: A comment on Nathoo, Kilshaw, and Masson (2018). Journal of Mathematical Psychology, 88, 27-31. doi:10.1016/j.jmp.2018.11.002

Heck, D. W., & Davis-Stober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 70-87. doi:10.1016/j.jmp.2019.03.004

Heck, D. W., Overstall, A., Gronau, Q. F., & Wagenmakers, E. (2019). Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. Statistics & Computing, 29, 631-643. doi:10.1007/s11222-018-9828-0

Klein, S. A., Heck, D. W., Reese, G., & Hilbig, B. E. (2019). On the relationship between Openness to Experience, political orientation, and pro-environmental behavior. Personality and Individual Differences, 138, 344-348. doi:10.1016/j.paid.2018.10.017

Kukken, N., Hütter, M., & Holland, R. W. (2019). Are there two independent evaluative conditioning effects in relational paradigms? Dissociating the effects of CS-US pairings and their meaning. Cognition & Emotion. doi: 10.1080/02699931.2019.1617112

Miller J. & Ulrich R. (2019). The quest for an optimal alpha. PLoS ONE 14(1): e0208631. doi: 10.1371/journal.pone.0208631

Radev, S. T., Mertens, U. K., Voss, A. and Köthe, U. (2019). Towards end‐to‐end likelihood‐free inference with convolutional neural networks. British Journal of Mathematical and Statistical Psychology doi:10.1111/bmsp.12159

Thielmann, I., & Hilbig, B. E. (2019). Nomological consistency: A comprehensive test of the equivalence of different trait indicators for the same constructs. Journal of Personality, 87(3), 715-730. doi: 10.1111/jopy.12428

2018

Erdfelder, E. & Ulrich, R. (2018). Zur Methodologie von Replikationsstudien. (On the methodology of replication studies.) Psychologische Rundschau, 69, 3-21. doi: 10.1026/0033-3042/a000387

Heck, D. W., Arnold, N. R., & Arnold, D. (2018). TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling. Behavior Research Methods, 50(1), 264–284. doi: 10.3758/s13428-017-0869-7

Heck, D. W., Erdfelder, E., & Kieslich, P. J. (2018). Generalized processing tree models: Jointly modeling discrete and continuous variables. Psychometrika, 83, 893–918. doi:10.1007/s11336-018-9622-0

Heck, D. W., Hoffmann, A., & Moshagen, M. (2018). Detecting nonadherence without loss in efficiency: A simple extension of the crosswise model. Behavior Research Methods, 50, 1895-1905. doi:10.3758/s13428-017-0957-8 

Heck, D. W., & Moshagen, M. (2018). RRreg: An R package for correlation and regression analyses of randomized response data. Journal of Statistical Software, 85 (2), 1-29. doi: 10.18637/jss.v085.i02   [Link to RRreg package on CRAN]

Heck, D. W., Thielmann, I., Moshagen, M., & Hilbig, B. E. (2018). Who lies? A large-scale reanalysis linking basic personality traits to unethical decision making. Judgment and Decision Making, 13, 356–371. Retrieved from http://journal.sjdm.org/18/18322/jdm18322.pdf

Kuhlmann, B. G., & Undorf, M. (2018). Is all metamemory monitoring spared from aging? A dual-process examination. Psychology and Aging, 33, 1152–1167. doi:10.1037/pag0000318

Mascarenhas, M. F., Dübbers, F., Hoszowska, M.,  Köseoğlu, A.,  Karakasheva, R. B. Topal, A. & Izydorczyk, D., Lemoine, J. E. (2018). The Power of Choice: A Study Protocol on How Identity Leadership Fosters Commitment Toward the Organization. Frontiers in Psychology, 9, 1677. doi: 10.3389/fpsyg.2018.01677

Mertens, U. K., Voss, A., & Radev, S. T. (2018). ABrox—A user-friendly Python module for approximate Bayesian computation with a focus on model comparison. PloS one, 13(3). doi: 10.1371/journal.pone.0193981

Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (2018). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. Applied Psychological Measurement, 42(2), 116–135.doi: 10.1177/0146621617710465

Plieninger, H., & Heck, D. W. (2018). A new model for acquiescence at the interface of psychometrics and cognitive psychology. Multivariate Behavioral Research, 53(5), 633-654. doi: 10.1080/00273171.2018.1469966

Ulrich, R., Miller, J., & Erdfelder, E. (2018). Effect size estimation from t statistics in the presence of publication bias: A brief review of existing approaches with some extensions. Zeitschrift für Psychologie, 226, 56-80. doi: 10.1027/2151-2604/a000319


Talks

2019

Bott, F. (2019, June). The Influence of Information Sampling on the Pseudocontingency Effect. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

Bott, F. & Meiser, T. (2019). Decision Making Based on Pseudocontingencies – A Matter of Information Sampling. In 61. Tagung experimentell arbeitender Psychologen. London, United Kingdom.

Hartmann, R. , Klauer, K. C., & Johannsen, L. (2019) Response Time Extended Multinomial Processing Trees in R. In 50th Meeting of the European Mathematical Psychology Group (EMPG), Heidelberg.

Hartmann, R. (2019, June). Response Time Extended Multinomial Processing Tree (RT-MPT) Models in R. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

Heck, D. W. & Davis-Stober, C. P. (2019). Bayesian Inference for Multinomial Models with Linear Inequality Constraints In 50th Meeting of the European Mathematical Psychology Group (EMPG), Heidelberg.

Kukken, N. (2019, June). Are there two independent evaluative conditioning effects in relational paradigms? Dissociating the effects of CS-US pairings and their meaning. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

Schnuerch, M. (2019). Efficiently testing sensitive attributes: A sequential randomized response technique. In 61. Tagung experimentell arbeitender Psychologen. London, United Kingdom.

Schnuerch, M. (2019, June). Sequential Hypothesis Tests for Multinomial Processing Tree Models. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

Symeonidou, N. & Kuhlmann, B. G. (2019). Source reinstatement facilitates source retrieval. In 61. Tagung experimentell arbeitender Psychologen. London, United Kingdom.

von Krause, M. (2019, June). Using the diffusion model to assess dark personality. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

Voormann, A. (2019, June). Investigating mechanisms underlying paired-word recognition using continuous and discrete-state models. Talk given at the 34th IOPS/SMiP Summer Conference, Utrecht, the Netherlands.

2018

Heck, D. W. (2018). A caveat on using the Savage-Dickey density ratio in regression models. Amsterdam, Netherlands: Department of Psychology (Eric-Jan Wagenmakers).

Heck, D. W. (2018). Bayesian hierarchical multinomial processing tree models: A general framework for cognitive psychometrics. In 51. Kongress der Deutschen Gesellschaft für Psychologie. Frankfurt, Germany.

Heck, D. W. (2018). Computing Bayes factors for cognitive models: A caveat on the Savage-Dickey density ratio. In Psychonomic Society 59th Annual Meeting. New Orleans, USA.

Heck, D. W. (2018). TreeBUGS: Hierarchical multinomial processing tree models in R. Tübingen, Germany: Psychoco 2018: International Workshop on Psychometric Computing, Tübingen, Germany.

Heck, D. W., Erdfelder, E., & Kieslich, P. J. (2018). Jointly modeling mouse-trajectories and accuracies with generalized  processing trees. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Kukken, N. & Hütter, M. (2018). Dissociating Intentional and Unintentional Learning Effects in Evaluative Conditioning. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Kukken, N., Holland, R. W., & Hütter, M. (2018). Dissociating the Effects of Implications and Pairings in a Relational Evaluative Conditioning Paradigm. Talk given at the European Social Cognition Network's Conference (ESCON), Cologne, Germany.

Schnuerch, M. & Erdfelder, E. (2018). Controlling statistical decision errors with minimal costs: Relative efficiency of sequential probability ratio t-tests vs. Bayesian t-tests. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Schnuerch, M., Heck, D. W., & Erdfelder, E. (2018). Waldian t tests: A sequential Bayes factor design for accepting and rejecting the null hypothesis with controlled error probabilities. In 2018 European Mathematical Psychology Group Meeting. Genoa, Italy.

2017

Bott, F., Fleig, H., & Meiser, T. (2017). The Role of Causal Expectations in Contingency Learning and (Biased) Choice Behavior. In 59. Tagung experimentell arbeitender Psychologen. Dresden, Germany.

Heck, D. W. (2017). Extending multinomial processing tree models to response times: The case of the recognition heuristic. Max Planck Institute, Berlin, Germany: Colloquium on Adaptive Rationality (Thorsten Pachur)

Heck, D. W., Arnold, N. R., & Arnold, D. (2017). TreeBUGS: A user-friendly software for hierarchical multinomial processing tree modeling. In Meeting of the Society of Computers in Psychology. Vancouver, Canada.

Heck, D. W., Erdfelder, E., & Kieslich, P. J. (2017). Modeling mouse-tracking trajectories with generalized processing tree models. In 50th Annual Meeting of the Society for Mathematical Psychology. Warwick, United Kingdom.


Posters

2019

Czink, M. (2019, June). A closer look at the temporal aspects of recovery. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Frick, S. (2019, June). Comparing information in the multidimensional forced-choice and the true-false format. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Grommisch, G. (2019, June). Modeling Individual Differences in Emotion Regulation Repertoire in Daily Life with Multilevel Latent Profile Analysis. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Hasselhorn, K. (2019, June). Reactivity effects in ambulatory assessment Effects of participant burden on intraindividual variability. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Horsten, L. (2019, June). The Dark Core of Personality: Dissociating D from Honesty-Humility. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Izydorcyck, D. (2019, June). Measuring Rule- and Exemplar-based Processes in Judgment. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Johannsen, Lea (2019, June). Modelling Sequential Dependencies in Reaction Time Data: Extending the Diffusion Decision Model. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Radev, S.T. (2019, June). Taming the Intractable: Deep Learning for Universal Parameter Estimation. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Reiber, F. (2019, June). Modeling Non-compliance in the Randomized Response Technique using Unrelated Questions. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Symeonidou, N. (2019, June). Emotional source memory: (Why) Are emotional sources remembered better? Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Verliefde, T. (2019, June). Do Acquaintances Elicit Ambivalent Priming Effects? Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

Voormann, A., Spektor, M.S., & Klauer, K. C. (2019). Investigating paired word recognition: A comparison of continuous and discrete-state models. In 61. Tagung experimentell arbeitender Psychologen. London, UK.

Wiegelmann, M. (2019, June). Chronotype and work: A longitudinal perspective. Poster presented at the 34th IOPS/SMiP Summer Conference. Utrecht, the Netherlands.

2018

Berkessel, J. & Funk, F. (2018). The Influence of Perceived Remorse on Source Memory for Faces: A Multinomial Processing Tree Approach. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Bott, F. & Meiser, T. (2018). Contingency Learning and Choice-Behavior Based on Self-Directed and Other-Directed Information Sampling. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Hartmann, R. (2018). Recovering Rasch Model Parameters when the True Latent Traits are not Normally Distributed: Comparison of Bayesian and Likelihood-Based Approaches. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Pessach, D. & Klauer, K. C. (2018). Base Rate Task: Not a Measure of Logical Processing. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Schnuerch, M., & Wulff, L. (2018). As you like it: Social value affects recognition memory. In 7. Doktorandenworkshop Allgemeine Psychologie (A-Dok). Mainz, Germany.

von Krause, M., Lerche, V., Frischkorn, G., Schubert, A.-L., & Voss, A. (2018). The diffusion model can be used to analyse slow response time tasks. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

Voormann, A., Dittrich, K., Schimpf, N., & Klauer, K. C. (2018). Examining the mechanisms underlying the item-specific proportion congruent effect using the process dissociation procedure. In 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

2017

Heck, D. W., & Erdfelder, E. (2017). A generalized processing tree framework for discrete-state modeling of discrete and continuous variables. In Psychonomic Society 58th Annual Meeting. Vancouver, Canada.

Heck, D. W., Hilbig, B. E., & Moshagen, M. (2017). Formalizing and comparing psychologically plausible models of multiattribute decisions. In Meeting of the Society of Judgment and Decision Making. Vancouver, Canada.