Peer-reviewed journal articles

Henrich, F., & Klauer, K. C. (in press). Modeling truncated and censored data with the diffusion model in Stan. Behavior Research Methods.

Kelber, P. & Ulrich, R. (in press). Evaluating three independent-channels models of temporal-order and simultaneity judgment. Cognitive Psychology.

Kelber, P. & Ulrich, R. (in press). Evidence against independence of peripheral latencies and central threshold in temporal-order perception. Psychonomic Bulletin & Review.

Alagöz, Ö. E. C., Meiser, T., & Khorramdel, L. (2025) Disentangling individual differences in cognitive response mechanisms for rating scale items: A flexible-mixture multidimensional IRTree approach. Behavior Research Methods57(256). https://doi.org/10.3758/s13428-025-02778-0

Debelak, R., Meiser, T., & Gernand, A. (2025). Investigating heterogeneity in IRTree models for multiple response processes with score-based partitioning. British Journal of Mathematical and Statistical Psychology, 78(2), 420–439. https://doi.org/10.1111/bmsp.12367

Hasselhorn, K., Ottenstein, C., & Lischetzke, T. (2025). Modeling careless responding in ambulatory assessment studies using multilevel latent class analysis: Factors influencing careless responding. Psychological Methods, 30(2), 374–392. https://doi.org/10.1037/met0000580

Hato, T., Schumacher, L., Radev, S.T., & Voss, A. (2025). Lévy Versus Wiener: Assessing the Effects of Model Misspecification on Diffusion Model Parameters. Comput Brain Behav. Advance online publication. doi.org/10.1007/s42113-025-00248-6

Kelber, P., Mittelstädt, V., & Ulrich, R. (2025). Interplay of aging and practice in conflict processing: A big-data diffusion-model analysis. Psychology and Aging, 40(1), 66–85. https://doi.org/10.1037/pag0000848

Kelber, P., & Ulrich, R. (2025). Perceptual-moment theories. Psychological Review. Advance online publication. https://doi.org/10.1037/rev0000586

Kelber, P., Ulrich, R., Mackenzie, I. G., Jeschke, M. G., & Mittelstädt, V. (2025). Proactive control adaptation in Stroop tasks reflects adjustments in the strength of distractor suppression. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. https://doi.org/10.1037/xlm0001520

Liu, X., Bröder, A., & Singmann, H. (2025). Evaluating the Role of Mental Sampling in Probability Judgments: Illogical Rankings Occur in a Predictable Manner. Cognition, 263, Article 106125. https://doi.org/10.1016/j.cognition.2025.106125

Meyer-Grant, C. G.*, & Jakob, M.* (2025). Ranking tasks in recognition memory: A direct test of the two-high-threshold contrast model. Journal of Experimental Psychology: General, 154(5), 1445–1455. https://doi.org/10.1037/xge0001700

[* Shared first authorship]

Scholz, D. D.*, Kraus, J.*, & Miller, L. (2025). Measuring the propensity to trust in automated technology: Examining similarities to dispositional trust in other humans and validation of the PTT-A scale. International Journal of Human–Computer Interaction, 41(2), 970–993. https://doi.org/10.1080/10447318.2024.2307691
[*shared first authorship]

Schreiner, M. R., Quevedo Pütter, J., & Rebholz, T. R. (2025). Time for an update: Belief updating based on ambiguous scientific evidence. Zeitschrift für Psychologie/Journal of Psychology, 233(1), 17–29. https://doi.org/10.1027/2151-2604/a000571

Schumacher, L., Schnuerch, M., Voss, A., & Radev, S. T. (2025). Validation and comparison of non-stationary cognitive models: A diffusion model application. Computational Brain & Behavior, 8, 191–210. https://doi.org/10.1007/s42113-024-00218-4

Seitz, T., Alagöz, Ö. E. C., & Meiser, T. (2025). Disentangling qualitatively different faking strategies in high-stakes personality assessments: A mixture extension of the multidimensional nominal response model. Educational and Psychological Measurement. Advance online publication. https://doi.org/10.1177/00131644251341843

Seitz, T., Spengler, M., & Meiser, T. (2025). “What if applicants fake their responses?”: Modeling faking and response styles in high-stakes assessments using the multidimensional nominal response model. Educational and Psychological Measurement, 85(4), 747–782. https://doi.org/10.1177/00131644241307560

Smith, P., & Ulrich, R. (2025). Decomposing delta plots: Exploring the time course of the congruency effect using inhibition and facilitation curves. Psychological Research, 89(1), 52. https://doi.org/10.1007/s00426-024-02075-z

Bißantz, S., Frick, S., Melinscak, F., Iliescu, D., & Wetzel, E. (2024). The potential of machine learning methods in psychological assessment and test construction. European Journal of Psychological Assessment, 40(1), 1–4. https://doi.org/10.1027/1015-5759/a000817

Elsemüller, L., Schnuerch, M., Bürkner, P.-C., & Radev, S. T. (2024). A deep learning method for comparing Bayesian hierarchical models. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000645

Erdfelder, E., Nagel, J., Heck, D. W., & Petras, N. (2024). Uncovering null effects in null fields: The case of homeopathy. Journal of Clinical Epidemiology, 166, Article 111216. https://doi.org/10.1016/j.jclinepi.2023.11.006

Erdfelder, E., Quevedo Pütter, J. & Schnuerch, M. (2024). On aggregation invariance of multinomial processing tree models. Behavior Research Methods, 56, 8677-8694. https://doi.org/10.3758/s13428-024-02497-y

Henrich, F., Hartmann, R., Pratz, V., Voss, A., & Klauer, K. C. (2024). The seven-parameter diffusion model: An implementation in Stan for Bayesian Analyses. Behavior Research Methods, 56, 3102-3116. https://doi.org/10.3758/s13428-023-02179-1

Izydorczyk, D. & Bröder, A. (2024). What is the airspeed velocity of an unladen swallow? Modeling numerical judgments of realistic stimuli. Psychonomic Bulletin & Review, 31(3), 1078-1092. https://doi.org/10.3758/s13423-023-02331-0

Johansson, R. C. G., Kelber, P. & Ulrich, R. (2024). Speeded classification of visual events is sensitive to crossmodal intensity correspondence. Journal of Experimental Psychology: Human Perception and Performance, 50(6), 554–569. https://doi.org/10.1037/xhp0001183

Johansson, R. C. G. & Ulrich, R. (2024). Serial processing of proximity groups and similarity groups. Attention, Perception, & Psychophysics, 86(4), 1303-1317. https://doi.org/10.3758/s13414-024-02861-2

Kelber, P., & Ulrich, R. (2024). Independent-channels models of temporal-order judgment revisited: A model comparison. Attention, Perception, & Psychophysics, 86(6), 2187-2209. https://doi.org/10.3758/s13414-024-02915-5

Koch, T. J. S., Arnold, M., Völker, J., & Sonnentag, S. (2024). Eat healthy, feel better: Are differences in employees’ longitudinal healthy-eating trajectories reflected in better psychological well-being? Applied Psychology: Health and Well-Being, 16(3), 1305–1325. https://doi.org/10.1111/aphw.12529

Koch, T. J. S., Nesher Shoshan, H., Völker, J., & Sonnentag, S. (2024). Psychological detachment matters right after work: Engaging in physical exercise after stressful workdays. International Journal of Stress Management, 31(3), 266–278. https://doi.org/10.1037/str0000312

Koch, T. J. S., Völker, J., & Sonnentag, S. (2024). Healthy and successful: Health-behavior goal striving in daily work life. Stress and Health, 40(2), Article e3295. https://doi.org/10.1002/smi.3295

Kraus, J., Miller, L., Klumpp, M., Babel, F., Scholz, D., Merger, J., & Baumann, M. (2024). On the role of beliefs and trust for the intention to use service robots: An integrated trustworthiness beliefs model for robot acceptance. International Journal of Social Robotics, 16(6), 1223–1246. https://doi.org/10.1007/s12369-022-00952-4

Kupffer, R., Frick, S., & Wetzel, E. (2024). Detecting careless responding in multidimensional forced-choice questionnaires. Educational and Psychological Measurement, 84(5), 887–926. https://doi.org/10.1177/00131644231222420

Mayer, M., & Heck, D. W. (2024). Sequential collaboration: The accuracy of dependent, incremental judgments. Decision, 11(1), 212–237.https://doi.org/10.1037/dec0000193

Merhof, V., Böhm, C. M., & Meiser, T. (2024). Separation of traits and extreme response style in IRTree models: The role of mimicry effects for the meaningful interpretation of estimates. Educational and Psychological Measurement, 84(5), 927–956. https://doi.org/10.1177/00131644231213319

Petras, N., Dantlgraber, M., & Reips, U. D. (2024). Illustrating psychometric tests, scales, and constructs: An R package for Item Pool Visualization. Behavior Research Methods, 56(2), 639–650. https://doi.org/10.3758/s13428-022-02052-7

Petras, N. & Meiser, T. (2024). Problems of domain factors with small factor loadings in Bi-factor models. Multivariate Behavioral Research, 59(1), 123–147.  https://doi.org/10.1080/00273171.2023.2228757

Rebholz, T. R., Biella, M., & Hütter, M. (2024). Mixed-effects regression weights for advice taking and related phenomena of information sampling and utilization. Journal of Behavioral Decision Making, 37(2), Article e2369. https://doi.org/10.1002/bdm.2369

Rebholz, T. R., Koop, A., & Hütter, M. (2024). Conversational User Interfaces: Explanations and Interactivity Positively Influence Advice Taking From Generative Artificial Intelligence. Technology, Mind, and Behavior, 5(4). https://doi.org/10.1037/tmb0000136

Reiber, F., Bryce, D., & Ulrich, R. (2024). Self-protecting responses in randomized response designs: A survey on intimate partner violence during the COVID-19 pandemic. Sociological Methods and Research, 53(1),  296–327. https://doi.org/10.1177/00491241211043138

Schmitt, M. C., Vogelsmeier, L. V. D. E., Erbas, Y., Stuber, S., & Lischetzke, T. (2024). Exploring within-person variability in qualitative negative and positive emotional granularity by means of latent Markov factor analysis. Multivariate Behavioral Research, 59(4), 781–800. https://doi.org/10.1080/00273171.2024.2328381

Schnuerch, M., Haaf, J. M., Sarafoglou, A., & Rouder, J. N. (2022). Meaningful comparisons with ordinal-scale items. Collabra: Psychology, 8(1), Article 28594. https://doi.org/10.1525/collabra.38594

Schnuerch, M., Heck, D. W., & Erdfelder, E. (2024). Waldian t tests: Sequential Bayesian t tests with controlled error probabilities. Psychological Methods, 29(1), 99–116. https://doi.org/10.1037/met0000492

Scholz, D. D., Bader, M., Betsch, C., Böhm, R., Lilleholt, L., Sprengholz, P., Zettler, I. (2024). The moderating role of trust in pandemic-relevant institutions on the relation between pandemic fatigue and vaccination intentions. Journal of Health Psychology, 29(4), 358–364. https://doi.org/10.1177/13591053231201038

Scholz, D. D., Zimmermann, J., Moshagen, M., Zettler, I., & Hilbig, B. E. (2024). Theoretical and empirical integration of ‘dark’ traits and socially aversive personality psychopathology. Journal of Personality Disorders, 38(3), 241–267. https://doi.org/10.1521/pedi.2024.38.3.241

Schreiner, M. R., Bröder, A., & Meiser, T. (2024). Agency effects on the binding of event elements in episodic memory. Quarterly Journal of Experimental Psychology. 77(6), 1201-1220. https://doi.org/10.1177/17470218231203951

Seitz, T., Wetzel, E., Hilbig, B. E., & Meiser, T. (2024). Using the multidimensional nominal response model to model faking in questionnaire data: The importance of item desirability characteristics. Behavior Research Methods, 56(8), 8869–8896. https://doi.org/10.3758/s13428-024-02509-x

Smith, P., & Ulrich, R. (2024). The neutral condition in conflict tasks: On the violation of the midpoint assumption in reaction time trends. Quarterly Journal of Experimental Psychology, 77(5), 1023-1043. https://doi.org/10.1177/17470218231201476

Ulitzsch, E., Henninger, M., & Meiser, T. (2024). Differences in response-scale usage are ubiquitous in cross-country comparisons and a potential driver of elusive relationships. Scientific Reports, 14(1), Article 10890. https://doi.org/10.1038/s41598-024-60465-0

Völker, J., Koch, T. J. S., Wiegelmann, M., & Sonnentag, S. (2024). Mind the misalignment: The moderating role of daily social sleep lag in employees' recovery processes. Journal of Organizational Behavior, 45(5), 684–701. https://doi.org/10.1002/job.2777

Völker, J., Wiegelmann, M., Koch, T. J. S., & Sonnentag, S. (2024). It's Monday again: Weekend sleep differentially relates to the workweek via reattachment on Monday. Journal of Organizational Behavior, 45(6), 800–817. https://doi.org/10.1002/job.2788

Wieschen, E.M., Makani, A., Radev, S.T., Voss, A., & Spaniol, J. (2024). Age-related differences in decision-making: Evidence accumulation is more gradual in older age. Experimental Aging Research, 50(5) 537–549. https://doi.org/10.1080/0361073X.2023.2241333

Alagöz, Ö. E. C., & Meiser, T. (2023). Investigating Heterogeneity in Response Strategies: A Mixture Multidimensional IRTree Approach. Educational and Psychological Measurement, 84(5), 957–993. https://doi.org/10.1177/00131644231206765 

Arnold, M., Casper, A., & Sonnentag, S. (2023). Daily trajectories of evening recovery experiences and their role for next-day mood. Journal of occupational health psychology, 28(5), 291–309. https://doi.org/10.1037/ocp0000359

Arnold, M., & Sonnentag, S. (2023). Time matters: The role of recovery for daily mood trajectories at work. Journal of Occupational and Organizational Psychology, 96(4), 754–785. https://doi.org/10.1111/joop.12445

Fenn, J., Helm, J. F., Höfele, P., Kulbe, L., Ernst, A., & Kiesel, A. (2023). Identifying key-psychological factors influencing the acceptance of yet emerging technologies–A multi-method-approach to inform climate policy. PLOS Climate, 2(6), Article e0000207. https://doi.org/10.1371/journal.pclm.0000207

Frick, S., Brown, A. A., & Wetzel, E. (2023). Investigating the normativity of trait estimates from multidimensional forced-choice data. Multivariate Behavioral Research, 58(1), 1–29. https://doi.org/10.1080/00273171.2021.1938960

Hartmann, R., Meyer-Grant, C. G., & Klauer, K. C. (2023). An adaptive rejection sampler for sampling from the Wiener diffusion model. Behavior research methods, 55(5), 2283–2296. https://doi.org/10.3758/s13428-022-01870-z

Hoogeveen, S., Sarafoglou, A., ..., Frick, S., ... , Izydorczyk, D., ..., Laukenmann, R., ..., Quevedo Pütter, J., ..., Schmitt, M.C., ..., Schnuerch, M., ..., Schreiner, M.R., ..., Stuber, S., & Wagenmakers, E.-J. (2023). A many-analysts approach to the relation between religiosity and well-being. Religion, Brain & Behavior, 13(3), 237–283. https://doi.org/10.1080/2153599X.2022.2070255 

Horsten, L. K., Thielmann, I., Moshagen, M., Zettler, I., Scholz, D., & Hilbig, B. E. (2023). Testing the equivalence of the aversive core of personality and a blend of agreeableness(-related) items. Journal of personality, 92(2), 393–404. https://doi.org/10.1111/jopy.12830

Mayer, M., Broß, M., & Heck, D. W. (2023). Expertise determines the frequency and accuracy of contributions in sequential collaboration. Judgment and Decision Making, 18, Article E2. https://dx.doi.org/10.1017/jdm.2023.3

Mayer, M., & Heck, D. W. (2023). Cultural consensus theory for two-dimensional location judgments. Journal of Mathematical Psychology, 113, Article 102742. https://dx.doi.org/10.1016/j.jmp.2022.102742

Merhof, V., & Meiser, T. (2023). Dynamic response style effects: Accounting for response process heterogeneity in IRTree decision nodes. Psychometrika, 88(4), 1354–1380. https://doi.org/10.1007/s11336-023-09901-0

Meyer-Grant, C. G., Cruz, N., Singmann, H., Winiger, S., Goswami, S., Hayes, B. K., & Klauer, K. C. (2023). Are logical intuitions only make-believe? Reexamining the logic-liking effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 49(8), 1280–1305. https://doi.org/10.1037/xlm0001152

Meyer-Grant, C. G. & Klauer, K. C. (2023). Does ROC-asymmetry reverse when detecting new stimuli? Reinvestigating whether the retrievability of mnemonic information is task-dependent. Memory & Cognition, 51(1), 160–174. https://doi.org/10.3758/s13421-022-01346-7

Radev, S. T., Schmitt, M., Schumacher, L., Elsemüller, L., Pratz, V., Schälte, Y., Köthe, U., & Bürkner, P.-C. (2023). Bayesflow: Amortized bayesian workflows with neural networks. Journal of Open Source Software, 8(89), Article 5702. https://doi.org/10.21105/joss.05702

Reiber, F., Pope, H., & Ulrich, R. (2023). Cheater detection using the unrelated question model. Sociological Methods and Research, 52(1), 389–411. https://doi.org/10.1177/0049124120914919

Rouder, J. N., Schnuerch, M., Haaf, J. M., & Morey, R. D. (2023). Principles of model specification in ANOVA Designs. Computational Brain & Behavior, 6, 50–63. https://doi.org/10.1007/s42113-022-00132-7

Scholz, D. D., Thielmann, I., & Hilbig, B. E. (2023). Down to the core: The role of the common core of dark traits for aversive relationship behaviors. Personality and Individual Differences, 213, Article 112263. https://doi.org/10.1016/j.paid.2023.112263

Schreiner, M. R. & Hütter, M. (2023). The influence of social status on memory: No evidence for effects of social status on event element binding. Social Cognition, 41(5), 447–466. https://doi.org/10.1521/soco.2023.41.5.447

Schreiner, M. R. & Meiser, T. (2023). Measuring binding effects in event-based episodic representations. Behavior Research Methods, 55, 981–996. https://doi.org/10.3758/s13428-021-01769-1 

Schreiner, M. R., Meiser, T., & Bröder, A. (2023). The binding structure of event elements in episodic memory and the role of animacy. Quarterly journal of experimental psychology, 76(4), 705–730. https://doi.org/10.1177/17470218221096148

Schreiner, M. R., Mercier, B., Frick, S., Wiwad, D., Schmitt, M. C., Kelly, J. M., Quevedo Pütter, J. (2023). Measurement issues in the many analysts religion project [Peer commentary on “A many-analysts approach to the relation between religiosity and well-being” by S. Hoogeveen et al.]. Religion, Brain & Behavior, 13(3), 339–341.  https://doi.org/10.1080/2153599X.2022.2070260

Schumacher, L., & Voss, A., (2023). Duration discrimination: A diffusion decision modeling approach. Attention, Perception, & Psychophysics, 85(2), 560–577. https://doi.org/10.3758/s13414-022-02604-1

Schumacher, L., Bürkner, P.-C., Voss, A., Köthe, U., & Radev, S. T. (2023). Neural superstatistics for Bayesian estimation of dynamic cognitive models. Scientific Reports, 13(1), Article 13778. https://doi.org/10.1038/s41598-023-40278-3

Sonnentag, S., Kottwitz, M. U., Koch, T. J. S., & Völker, J. (2023). Enrichment and conflict between work and health behaviors: New scales for assessing how work relates to physical exercise and healthy eating. Occupational Health Science, 7(2), 251–296. https://doi.org/10.1007/s41542-022-00134-8

Völker, J., Casper, A., Koch, T. J. S., & Sonnentag, S. (2023). It’s a match: The relevance of matching chronotypes for dual-earner couples’ daily recovery from work. Journal of Occupational Health Psychology, 28(3), 174–191. https://doi.org/10.1037/ocp0000351

Wiegelmann, M., Völker, J., & Sonnentag, S. (2023). Sleep has many faces: The interplay of sleep and work in predicting employees’ energetic state over the course of the day. Journal of Occupational Health Psychology, 28(1), 52–63. https://doi.org/10.1037/ocp0000345 

Bader, M.*, Horsten, L. K.*, Hilbig, B. E., & Zettler, I., & Moshagen, M. (2022). Measuring the dark core of personality in German: Psychometric properties, measurement invariance, predictive validity, and self-other agreement. Journal of Personality Assessment, 104, 660–637. https://doi.org/10.1080/00223891.2021.1984931 

[*shared first-authorship]

Frick, S. (2022). Modeling faking in the multidimensional forced-choice format: The faking mixture model. Psychometrika, 87, 773–794 (2022). https://doi.org/10.1007/s11336-021-09818-6

Horsten, L. K., Hilbig, B. E., Thielmann, I., Zettler, I., & Moshagen, M. (2022). Fast, but not so Furious. On the Distinctiveness of a Fast Life History Strategy and the Common Core of Aversive Traits. Personality Science, 3, 1–19. doi.org/10.5964/ps.6879

Meyer-Grant, C. G.,& Klauer, K. C. (2022) Disentangling different aspects of between-item similarity unveils evidence against the ensemble model of lineup memory. Computational Brain & Behavior, 5, 509–526. https://doi.org/10.1007/s42113-022-00135-4 

Quevedo Pütter, J., & Erdfelder, E. (2022). Alcohol-induced retrograde facilitation? Mixed evidence in a preregistered replication and encoding-maintenance-retrieval analysis. Experimental Psychology, 69(6), 335–350. https://doi.org/10.1027/1618-3169/a000569

Radev, S. T., Mertens, U. K., Voss, A., Ardizzone, L., & Köthe, U. (2022). BayesFlow: learning complex stochastic models with invertible neural networks. IEEE Transactions on Neural Networks and Learning Systems, 33(4), 1452 – 1466. doi.org/10.1109/TNNLS.2020.3042395

Rebholz, T. R., & Hütter, M. (2022). The advice less taken: The consequences of receiving unexpected advice. Judgment and Decision Making, 17(4), 816–848. doi.org/10.1017/S1930297500008950

Reiber, F., Schnuerch, M., & Ulrich, R. (2022). Improving the efficiency of surveys with randomized response models: A sequential approach based on curtailed sampling. Psychological Methods, 27(2), 198–211. https://doi.org/10.1037/met0000353

Scholz, D. D., Hilbig, B. E., Thielmann, I., Moshagen, M. & Zettler, I. (2022). Beyond (low) Agreeableness: Towards a more comprehensive understanding of antagonistic psychopathology. Journal of personality. 90(6), 956–97. https://doi.org/10.1111/jopy.12708

Symeonidou, N., & Kuhlmann, B. G. (2022). Better memory for emotional sources? A systematic evaluation of source valence and arousal in source memory. Cognition & emotion, 36(2), 300–316. https://doi.org/10.1080/02699931.2021.2008323

von Krause, M., Radev, S., & Voss, A. (2022). Mental speed is high until age 60 as revealed by a model-based neural network analysis of big data. Nature: Human Behavior, 6, 700–708. https://doi.org/10.1038/s41562-021-01282-7

Bott, F. M., Kellen, D., & Klauer, K. C. (2021). Normative accounts of illusory correlations. Psychological Review, 128(5), 856–878.https://doi.org/10.1037/rev0000273

Erdfelder, E., & Schnuerch, M. (2021). On the efficiency of the independent segments procedure: A direct comparison with sequential probability ratio tests. Psychological methods, 26(4), 501–506. https://doi.org/10.1037/met0000404

Hartmann, R. & Klauer, K. C. (2021). Partial derivatives for the first-passage time distribution in Wiener diffusion models. Journal of Mathematical Psychology, 103, Article 102550. https://doi.org/10.1016/j.jmp.2021.102550

Hasselhorn, K., Ottenstein, C., & Lischetzke, T. (2021). The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment. Behavior Research Methods, 54, 1541-1558. https://doi.org/10.3758/s13428-021-01683-6

Hilbig, B. E., Moshagen, M., Horsten, L. K., & Zettler, I. (2021). Agreeableness is dead. Long live Agreeableness? Reply to Vize and Lynam. Journal of Research in Personality, 91, Article 104074. https://doi.org/10.1016/j.jrp.2021.104074

Horsten, L. K., Moshagen, M., Zettler, I., & Hilbig, B. E., (2021). Theoretical and empirical dissociations between the Dark Factor of Personality and low Honesty-Humility. Journal of Research in Personality, 95, Article 104154. https://doi.org/10.1016/j.jrp.2021.104154

Izydorczyk, D. & Bröder, A. (2021). Exemplar-based judgment or direct recall: On a problematic procedure for estimating parameters in exemplar models of quantitative judgment. Psychonomic Bulletin & Review. 28, 1495–1513. https://doi.org/10.3758/s13423-020-01861-1

Konicar, L., Radev, S. T., Prillinger, K., Klöbl, M., Diehm, R., Birbaumer, N., ... & Poustka, L. (2021). Volitional modification of brain activity in adolescents with Autism Spectrum Disorder: A Bayesian analysis of Slow Cortical Potential neurofeedback. NeuroImage: Clinical, 29, 1–10. https://doi.org/10.1016/j.nicl.2021.102557

Kroneisen, M., Bott, F. M., & Mayer, M. (2021). Remembering the bad ones: Does the source memory advantage for cheaters influence our later actions positively? Quarterly Journal of Experimental Psychology, 74(10),1669-1685. https://doi.org/10.1177/17470218211007822

Mertens, A., von Krause, M., Denk, A., & Heitz, T. (2021). Gender differences in eating behavior and environmental attitudes – The mediating role of the Dark Triad. Personality and Individual Differences, 168, Article 110359. https://doi.org/10.1016/j.paid.2020.110359

Meyer-Grant, C. G. & Klauer, K. C. (2021). Monotonicity of rank order probabilities in signal detection models of simultaneous detection and identification. Journal of Mathematical Psychology, 105, Article 102615. https://doi.org/10.1016/j.jmp.2021.102615

Nadarevic, L., Schnuerch, M., & Stegemann, M. (2021). Judging fast and slow: The truth effect does not increase under time-pressure conditions. Judgment and Decision Making, 16(5), 1234-1266. https://doi.org/10.1017/S193029750000841X

Radev, S. T., Graw, F., Chen, S., Mutters, N. T., Eichel, V. M., Bärnighausen, T., & Köthe, U. (2021). OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany. PLoS Computational Biology, 17(10), Article e1009472. https://doi.org/10.1371/journal.pcbi.1009472

Reuter, L., Fenn, J., Bilo, T. A., Schulz, M., Weyland, A. L., Kiesel, A., & Thomaschke, R. (2021). Leisure walks modulate the cognitive and affective representation of the corona pandemic: Employing Cognitive‐Affective Maps within a randomized experimental design. Applied Psychology: Health and Well‐Being, 13(4), 952–967. https://doi.org/10.1111/aphw.12283

Schmitt, M. C., Prestele, E., & Reis, D. (2021). Perfectionistic cognitions as antecedents of work engagement: Personal resources, personal demands, or both? Collabra: Psychology, 7(1), Article 25912. https://doi.org/10.1525/collabra.25912

Schnuerch, M., Nadarevic, L., & Rouder, J. N. (2021). The truth revisited: Bayesian analysis of individual differences in the truth effect. Psychonomic Bulletin & Review, 28, 750–765. doi.org/10.3758/s13423-020-01814-8

Stump, A., Rummel, J., & Voss, A. (2021). Is it all about the feeling? Affective and (meta-)cognitive mechanisms underlying the truth effect. Psychological Research, 86, 12–36. https://doi.org/10.1007/s00426-020-01459-1

Symeonidou, N., & Kuhlmann, B. G. (2021). A novel paradigm to assess storage of sources in memory: The source recognition test with reinstatement. Memory, 29(4), 507–523. https://doi.org/10.1080/09658211.2021.1910310

Theisen, M., Lerche, V., von Krause, M.*, & Voss, A. (2021). Age differences in diffusion model parameters: A meta-analysis. Psychological Research, 85, 2012–2021. doi.org/10.1007/s00426-020-01371-8

von Krause, M., Radev, S.T., Voss, A., Quintus, M., Egloff, B., & Wrzus, C. (2021). Stability and change in diffusion model parameters over two years. Journal of Intelligence, 9(2), Article 26. https://doi.org/10.3390/jintelligence9020026

Voormann, A., Spektor, M. S., & Klauer, K. C. (2021). The simultaneous recognition of multiple words: A process analysis. Memory and Cognition, 49,787–802. https://doi.org/10.3758/s13421-020-01082-w

Voormann, A., Rothe-Wulf, A., Starns, J. J., & Klauer, K.C. (2021). Does speed of recognition predict two-alternative forced-choice performance? Replicating and extending Starns, Dubé, and Frelinger (2018). Quarterly Journal of Experimental Psychology, 74(1), 122–134. https://doi.org/10.1177/1747021820963033

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. https://doi.org/10.1016/j.chb.2019.07.031

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. https://doi.org/10.1037/xlm0000840

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, Article 102388. https://doi.org/10.1016/j.jmp.2020.102388

D’Alessandro, M., Radev, S. T.,Voss, A., & Lombardi, L. (2020). A Bayesian brain model of adaptive behavior: an application to the Wisconsin Card Sorting Task. PeerJ, 8(e10316), 1–32 https://doi.org/10.7717/peerj.10316

Grommisch, G., Koval, P., Hinton, J. D. X., Gleeson, J., Hollenstein, T., Kuppens, P., & Lischetzke, T. (2020). Modeling individual differences in emotion regulation repertoire in daily life with multilevel latent profile analysis. Emotion, 20(8), 1462–1474. doi.org/10.1037/emo0000669

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. https://doi.org/10.3758/s13428-019-01318-x

Hartmann, R., & Klauer, K. C. (2020). Extending RT-MPTs to enable equal process times. Journal of Mathematical Psychology, 96, Article 102340. https://doi.org/10.1016/j.jmp.2020.102340

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. https://doi.org/10.3758/s13423-019-01663-0

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. https://doi.org/10.1177/0956797619866627

Kukken, N., Hütter, M., & Holland, R. W. (2020). Are there two independent evaluative conditioning effects in relational paradigms? Dissociating the effects of CS-US pairings and their meaning. Cognition & Emotion, 34(1), 170–187. https://doi.org/10.1080/02699931.2019.1617112 

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, 149(12), 2207–2249. https://doi.org/10.1037/xge0000774

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, Article 104516. https://doi.org/10.1016/j.appet.2019.104516

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, Article 103986. https://doi.org/10.1016/j.jrp.2020.103986

Nigg, C. R., Fuchs, R., Gerber, M., Jekauc, D., Koch, T., Krell-Roesch, J., ... & Sattler, M. C. (2020). Assessing physical activity through questionnaires–A consensus of best practices and future directions. Psychology of Sport and Exercise, 50, Article 101715. https://doi.org/10.1016/j.psychsport.2020.101715

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. https://doi.org/10.1111/epi.16454

Radev, S. T., Mertens, U. K., Voss, A., & Köthe, U. (2020). Towards end-to-end likelihood-free inference with convolutional neural networks. British Journal of Mathematical and Statistical Psychology, 73(1), 23–43. https://doi.org/10.1111/bmsp.12159

Schnuerch, M., & Erdfelder, E. (2020). Controlling decision errors with minimal costs: The sequential probability ratio t test. Psychological Methods, 25(2), 206–226. https://doi.org/10.1037/met0000234

Schnuerch, M., Erdfelder, E., & Heck, D. W. (2020). Sequential hypothesis tests for multinomial processing tree models. Journal of Mathematical Psychology, 95, Article 102326. http://doi.org/10.1016/j.jmp.2020.102326

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. https://doi.org/10.3390/jintelligence8030033

Wetzel, E., Frick, S., & Brown, A. (2020). 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, 33(2), 156–170. doi.org/10.1037/pas0000971

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. https://doi.org/10.1037/pas0000781

Wetzel, E., Frick, S., & Greiff, S. (2020). The multidimensional forced-choice format as an alternative for rating scales: Current state of the research. European Journal of Psychological Assessment, 36(4), 511–515. doi.org/10.1027/1015-5759/a000609

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. https://doi.org/10.20982/tqmp.16.2.p120

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. https://doi.org/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.  https://doi.org/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. https://doi.org/10.1027/2151-2604/a000383

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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/10.1016/j.jmp.2019.03.004

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. https://doi.org/10.1007/s42113-019-00035-0

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. https://doi.org/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. https://doi.org/10.1016/j.paid.2018.10.017

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, Article 102161. https://doi.org/10.1016/j.joep.2019.04.001

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.https://doi.org/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. (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. https://doi.org/10.1177/2515245919869583

Erdfelder, E. & Ulrich, R. (2018). Zur Methodologie von Replikationsstudien. (On the methodology of replication studies.) Psychologische Rundschau, 69, 3–21. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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

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. https://doi.org/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). https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/10.1027/2151-2604/a000319