Peer-reviewed journal articels

  • in press

    Bott, F. M., Kellen, D., & Klauer, K. C. (in press). Normative accounts of illusory correlations. Psychological Review.

    Izydorczyk, D. & Bröder, A. (in press). Exemplar-based judgment or direct recall: On a problematic procedure for estimating parameters in exemplar models of quantitative judgment. Psychonomic Bulletin & Review.

    Mertens, A., von Krause, M., Denk, A., & Heitz, T. (in press). Gender differences in eating behavior and environmental attitudes – The mediating role of the Dark Triad. Personality and Individual Differences, 168, 110359.

    Schnuerch, M., Nadarevic, L., & Rouder, J. N. (in press). The truth revisited: Bayesian analysis of individual differences in the truth effect. Psychonomic Bulletin & Review.

    Voormann, A., Rothe-Wulf, A., Starns J. J., & Klauer K. C. (in press). Does speed of recognition predict two-alternative forced-choice performance? Replicating and extending Starns, Dubé, and Frelinger (2018). Quarterly Journal of Experimental Psychology.

    Voormann, A., Spektor, M. S., & Klauer, K. C. (in press). The simultaneous recognition of multiple words: A process analysis. Memory and Cognition.

    Wetzel, E., Frick, S., & Brown, A. (in press). Is the multidimensional forced-choice format fake-proof? Comparing the susceptibility of the multidimensional forced-choice format and the rating scale format to socially desirable responding. Psychological Assessment.

  • 2020

    Appel, M., Izydorczyk, D., Weber, S., Mara, M., & Lischetzke, T. (2020). The uncanny of mind in a machine: Humanoid robots as tools, agents, and experiencers. Computers in Human Behavior, 102, 274–286.

    Bott, F. M., & Meiser, T. (2020). Pseudocontingency inference and choice: The role of information sampling. Journal of Experimental Psychology: Learning, Memory, and Cognition,46(9), 1624–1644.

    Bott, F. M., Heck, D. W., & Meiser, T. (2020). Parameter validation in hierarchical MPT models by functional dissociation with continuous covariates: An application to contingency inference. Journal of Mathematical Psychology, 98

    Hartmann, R., Johannsen, L., & Klauer, K. C. (2020). rtmpt: An R package for fitting response-time extended multinomial processing tree models. Behavior Research Methods, 52, 1313–1338.

    Hartmann, R., & Klauer, K. C. (2020). Extending RT-MPTs to Enable Equal Process Times. Journal of Mathematical Psychology, 96, 102340.

    Heck, D.W., & Erdfelder, E. (2020). Benefits of response time-extended multinomial processing tree models: A reply to Starns (2018). Psychonomic Bulletin & Review, 27, 571–580.

    Heck, D. W., Thielmann, I., Klein, S. A., & Hilbig, B. E. (2020). On the Limited Generality of Air Pollution and Anxiety as Causal Determinants of Unethical Behavior: Commentary on Lu, Lee, Gino, and Galinsky (2018). Psychological Science, 31(6), 741–747.

    Lerche, V., von Krause, M., Voss, A., Frischkorn, G. T., Schubert, A.-L., & Hagemann, D. (2020). Diffusion modeling and intelligence: Drift rates show both domain-general and domain-specific relations with intelligence. Journal of Experimental Psychology: General. Advance online publication.

    Mertens, A., von Krause, M., Meyerhöfer, S., Aziz, C., Baumann, F., Denk, A., ... & Maute, J. (2020). Valuing humans over animals–Gender differences in meat-eating behavior and the role of the Dark Triad.  Appetite, 146, 104516.

    Moshagen, M., Zettler, I., Horsten, L. K., & Hilbig, B. E. (2020). Agreeableness and the common core of dark traits are functionally different constructs. Journal of Research in Personality, 87, 103986.

    Pensel, M. C., Schnuerch, M., Elger, C. E., & Surges, R. (2020). Predictors of focal to bilateral tonic‐clonic seizures during long‐term video‐EEG monitoring. Epilepsia, 61(3), 489–497.

    Reiber, F., Pope, H., & Ulrich, R. (2020). Cheater detection using the unrelated question model. Sociological Methods and Research. Advance online publication.

    Reiber, F., Schnuerch, M., & Ulrich, R. (2020). Improving the efficiency of surveys with randomized response models: A sequential approach based on curtailed sampling. Psychological Methods. Advance online publication.

    Schnuerch, M., & Erdfelder, E. (2020). Controlling decision errors with minimal costs: The sequential probability ratio t test. Psychological Methods, 25(2), 206–226.

    Schnuerch, M., Erdfelder, E., & Heck, D. W. (2020). Sequential hypothesis tests for multinomial processing tree models. Journal of Mathematical Psychology, 95, 102326.

    von Krause, M., Lerche, V., Schubert, A.-L., & Voss, A. (2020). Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains? Journal of Intelligence, 8(3), 33.

    Wetzel, E., & Frick, S. (2020). Comparing the validity of trait estimates from the multidimensional forced-choice format and the rating scale format. Psychological Assessment, 32(3), 239–253.

    Wieschen, E. M., Voss, A., & Radev, S. (2020). Jumping to Conclusion? A Lévy Flight Model of Decision Making. The Quantitative Methods for Psychology, 16(2), 120–132.



  • 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

    Erdfelder, E. & Heck, D. W. (2019). Detecting evidential value and p-hacking with the p-curve tool: A word of caution. Zeitschrift für Psychologie, 227(4), 249-260. doi: 10.1027/2151-2604/a000383

    Grommisch, G., Koval, P., Hinton, J. D. X., Gleeson, J., Hollenstein, T., Kuppens, P., & Lischetzke, T. (2019). Modeling individual differences in emotion regulation repertoire in daily life with multilevel latent profile analysis. Emotion. Advance online publication. doi: 10.1037/emo0000669

    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/

    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/

    Heck, D. W., & Erdfelder, E. (2019). Maximizing the Expected Information Gain of Cognitive Modeling via Design Optimization. Computational Brain & Behavior, 2(3–4), 202–209.

    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

    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

    Schild, C., Heck, D. W., Ścigała, K. A., & Zettler, I. (2019). Revisiting REVISE: (Re)Testing unique and combined effects of REminding, VIsibility, and SElf-engagement manipulations on cheating behavior. Journal of Economic Psychology, 75, 102161.

    Ścigała, K. A., Schild, C., Heck, D. W., & Zettler, I. (2019). Who Deals With the Devil? Interdependence, Personality, and Corrupted Collaboration. Social Psychological and Personality Science, 10(8), 1019–1027.

    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. (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.


  • 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

    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

    Sonnentag, S. & Lischetzke, T. (2018). Illegitimate tasks reach into afterwork hours: A multilevel study. Journal of Occupational Health Psychology, 23, 248-261. doi: 10.1037/ocp0000077

    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