Statistical Auditing Group

Derks, K., Mensink, L., Smid, W., de Swart, J., & Wetzels, R. (2026). Practical benefits of discounting historical audit samples using normalized power priors. Journal of Accounting, Auditing & Finance.

Godmann, H. R., Mensink, L., Singla, P., Derks, K., & Wagenmakers, E.-J. (2026). Belief, evidence, and predictions in simple Bayesian acceptance sampling plans with JASP. PsyArXiv.

Derks, K., & de Swart, J. (2026). Bayesian adaptations of four popular audit sampling estimators. PsyArXiv.

Picogna, F., de Swart, J., Kaya, H., & Wetzels, R. (2026). How to choose a fairness measure: A decision-making workflow for auditors. International Journal of Auditing, 1-25.

Derks, K., Mensink, L., de Swart, J., Wagenmakers, E.-J., & Wetzels, R. (2026). Increasing efficiency in stratified audit sampling via Bayesian hierarchical modelling. International Journal of Auditing, 1-18.

Derks, K. (2025). Efficiëntere detailcontroles dankzij synergie van statistische en digitale technieken: profiteren van integraal beschikbare gegevens. Maandblad voor Accountancy en Bedrijfseconomie, 99(6), 365-377.

Derks, K., Mensink, L., & de Swart, J. (2025). Teaching advanced statistical modeling for evaluating audit samples: A demonstration using the open-source software JASP. OSF Preprints.

Bartoš, F. Sarafoglou, A., Godmann, H. R., Sahrani, A., Klein Leunk, D., Gui, P. Y., Voss, D., Ullah, K., Zoubek, M. J., Nippold, F., Aust, F., Vieira, F. F., Islam, C.-G., Zoubek, A. J., Shabani, S., Petter, J., Roos, I. B., Finnemann, A., Lob, A. B., Hoffstadt, M. F., Nak, J., de Ron, J., Derks, K., Huth, K., Terpstra, S., Bastelica, T., Matetovici, M., Ott, V. L., Zetea, A. S., Karnbach, K., Donzallaz, M. C., John, A., Moore, R. M., Assion, F., van Bork, R., Leidinger, T. E., Zhao, X., Karami Motaghi, A., Pan, T., Armstrong, H., Peng, T., Bialas, M., Pang, J. Y.-C., Fu, B., Yang, S., Lin, X., Sleiffer, D., Bognar, M., Aczel, B., & Wagenmakers, E.-J. (2025). Fair coins tend to land on the same side they started: Evidence from 350,757 flips. Journal of the Americal Statistical Association, 120(552), 2118-2127.

Derks, K., de Swart, J. J. B., & Wetzels, R. (2025). A hurdle approach to modeling audit samples with partial misstatements. PsyArXiv.

Derks, K., de Swart, J. J. B., Wagenmakers, E.-J., & Wetzels, R. (2025). The Bayesian approach to audit evidence: Quantifying statistical evidence using the Bayes factor. Auditing: A Journal of Practice & Theory, 44(1), 55-71.

Picogna, F., de Swart, J., & Wetzels, R. (2024). Addressing discrimination in artificial intelligence. Jaarsymposium VHMF 2024.

Derks, K., Mensink, L., de Swart, J., & Wetzels, R. (2024). Toepassing van data-analyse om de steekproef te rationaliseren. Maandblad voor Accountancy en Bedrijfseconomie, 98(4), 131-143.

Mensink, L., de Swart, J. J. B., Derks, K., & Wetzels, R. (2024). Enhancing efficiency and flexibility in audits through Bayesian optional stopping. PsyArXiv.

Steens, B., Bots, J., & Derks, K. (2024). Developing digital competencies of controllers: Evidence from the Netherlands. International Journal of Accounting Information Systems, 52.

van Liere, L., de Swart, J. J. B., van der Hel-van Dijk, E. C. J. M., & Wetzels, R. (2023). TaxTech: De daad bij het woord voegen: Fraudedetectiesystemen verankeren in de strategie van een organisatie. NL Fiscaal.

Derks, K. (2023). Bayesian Benefits for Auditing: A Proposal to Innovate Audit Methodology. PhD Thesis. Nyenrode Business Universiteit, Breukelen.

Derks, K., de Swart, J. J. B., & Wetzels, R. (2023). Open-source software als brug tussen de auditor en de statisticus. Maandblad voor Accountancy en Bedrijfseconomie, 97(1/2), 17-28.

van Buuren J., & Wijma, W. (2022). Over kwaliteitsborging van datagedreven controlemethodologie. Maandblad Voor Accountancy en Bedrijfseconomie, 96(1/2), 15-25.

Derks, K., de Swart, J. J. B., Wagenmakers, E.-J., & Wetzels, R. (2022). An impartial Bayesian hypothesis test for audit sampling. PsyArXiv.

Derks, K., de Swart, J. J. B., & Wetzels, R. (2022). Een Bayesiaanse blik op gestratificeerde steekproeven heeft voordelen voor de auditor. Maandblad voor Accountancy en Bedrijfseconomie, 96(1/2), 37-46.

Heck, D., Boehm, U., Böing-Messing, F. Bürkner, P. C., Derks, K., Dienes, Z., Fu, Q., Gu, X., Karimova, D., Kiers, H. A. L., Klugkist, I., Kuiper, R. M., Lee, M. D., Leenders, R., Leplaa, H. J., Linde, M., Ly, A., Meijerink-Bosman, M., Moerbeek, M., Mulder, J., Palfi, B., Schönbrod, F., Tendeiro, J. N., van den Bergh, D., Van Lissa, C. J., van Ravenzwaaij, D., Vanpaemel, W., Wagenmakers, E-.J., Williams, D. R., Zondervan-Zwijnenburg, M., & Hoijtink, H. (2022). A review of applications of the Bayes factor in psychological research. Psychological Methods., 97(1/2), 17-28.

van Nieuw Amerongen, N., Coskun, E., van Buuren, J. & Duits, H. B. (2022). The coherence of the auditor-client relationship quality and auditor tenure with client's perceptions on added-value in SME audits: A sociological perspective. Managerial Auditing Journal, 37 (3), 358-379.

van Buuren J., & Snoei, W. (2021). Over de diagnostische eigenschappen van Audit Quality Indicators. Maandblad Voor Accountancy en Bedrijfseconomie, 95(1/2), 33-45.

Derks, K., de Swart, J. J. B., van Batenburg, P., Wagenmakers, E.-J., & Wetzels, R. (2021). Priors in a Bayesian audit: How integration of existing information into the prior distribution can improve audit transparency and efficiency. International Journal of Auditing, 25(3), 621-636.

Derks, K., de Swart, J. J. B., Wagenmakers, E.-J., Wille, J., & Wetzels, R. (2021). JASP for Audit: Bayesian tools for the auditing practice. Journal of Open Source Software, 6(68), 2733.

van Doorn, J., van den Bergh, D., Dablander, F., van Dongen, N., Derks, K., Evans, N. J., Gronau, Q. F., Haaf, J., Kunisato, Y., Ly, A., Marsman, M., Sarafoglou, A., Stefan, A., & Wagenmakers, E.-J. (2021). Strong public claims may not reflect researchers' private convictions. Significance, 18(1), 44-45.

Haket, C., van der Rhee, B., & de Swart, J. J. B. (2020). Saving time and money and reducing carbon dioxide emissions by efficiently allocating customers. INFORMS Journal on Applied Analytics, 50(3), 153-165.

van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E., Derks, K., Dablander, F., Gronau, Q. F., Kucharský, Š., Gupta, A. R. K. N., Sarafoglou, A., Voekel, J. G., Stefan, A., Ly, A., Hinne, M., Matzke, D., & Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a Bayesian ANOVA in JASP. L' Année psychologique, 120(1), 73-96.

van Doorn, J., van den Bergh, D., Bohm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Gupta, A. R. K. N., Sarfoglou, A., Stefan, A., Voekel, J. G., & Wagenmakers, E.-J. (2020). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28, 813-826.

Landy, J. F., Jia, M., Ding, I. L., Viganola, D., Tierney, W., Dreber, A., Johannesson, M., Pfeiffer, T., Ebersole, C. R., Gronau, Q. F., Ly, A., van den Bergh, D., Marsman, M., Derks, K., Wagenmakers, E.-J., Proctor, A., Bartels, D. M., Baumann, C. W., Brady, W. J., Cheung, F., Cimpian, A., Dohle, S., Donnelan, M. B., Hahn, A., Hall, M. P., Jiménez-Leal, W., Johnson, D. J., Lucas, R. E., Monin, B., Montealegre, A., Mullen, E., Pang, J., Ray, J., Reneiro, D. A., Reynolds, J., Sowden, W., Storage, D., Su, R., Tworek, C. M., van Bavel, J. J., Walco, D., Will, J., Xi, X., Yam, K. C., Yang, X., Cunningham, W. A., Schweinsberg, M., Urwitz, M., The Crowdsourcing Hypothesis Test Collaboration, & Uhlmann, E. L. (2020). Crowdsourcing hypothesis tests: Making transparent how design choices shape research results. Psychological Bulletin, 146(5), 451-479.

Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharský, Š., Derks, K., Gronau, Q. F., Raj, A., Böhm, U., van Kesteren, E.-J., Hinne, M., Matzke, D., Marsman, M., & Wagenmakers, E.-J. (2020). The Bayesian methodology of Sir Harold Jeffreys as a practical alternative to the p value hypothesis test. Computational Brain & Behavior, 3, 153-161.

van Nieuw Amerongen, N., Evers, N., van Buuren, J. (2019). De waarderelevantie van kernpunten in de controleverklaring voor de kapitaalmarkten. Maandblad Voor Accountancy en Bedrijfseconomie, 93(1/2), 57-68.

van Buuren, J., Koch, C., van Nieuw Amerongen, N., & Wright, A. M. (2018). Evaluating the change process for business risk auditing: Legitimacy experiences of non-big 4 auditors. Auditing: A Journal of Practice & Theory, 37(2), 249–269.

Derks, K., Burger, J., van Doorn, J., Kossakowski, J. J., Matzke, D., Atticciati, L., Beitner, J., Benzesin, V., de Bruijn, A. L., Cohen, T. R. H., Cordesius, E. P. A., van Dekken, M., Delvendahl, N., Dobbelaar, S., Groenendijk, E. R., Hermans, M. E., Hiekkaranta, A. P., Hoekstra, R. H. A., Hoffmann, A. M., Hogenboom, S. A. M., Kahveci, S., Karaban, I. J., Kevenaar, S. T., te Koppele, J. L., Kramer, A-W., Kroon, E., Kucharský, Š., Lieuw-On, R., Lunansky, G., Matzen, T. P., Meijer, A., Nieper, A., de Nooij, L., Poelstra, L., van der Putten, W. J., Sarafoglou, A., Schaaf, J. V., van de Schraaf, S. A. J., van Schuppen, S., Schutte, M. H. M., Seibold, M., Slagter, S. K., Snoek, A. C., Stracke, S., Tamimy, Z., Timmers, B., Tran, H., Uduwa-Vidanalage, E. S., Vergeer, L., Vossoughi, L., Yücel, D. E., & Wagenmakers, E.-J. (2018). Network models to organize a dispersed literature: The case of misunderstanding analysis of covariance. Journal of European Psychology Students, 9, 48-57.

Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Selker, R., Gronau, Q. F., Dropmann, D., Boutin, B., Meerhoff, F., Knight, P., Raj, A., van Kesteren, E.-J., van Doorn, J., Smira, M., Epskamp, S., Etz, A., Matzke, D., de Jong, T., van den Bergh, D., Sarafoglou, A., Steingroever, H., Derks, K., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25(1), 58–76.

Witjas-Paalberends, E. R., van Laarhoven, L. P. M., van de Burgwal, L. H. M., Feilzer, J., de Swart, J. J. B., Claassen, E. & Jansen, W. T. M. (2018). Challenges and best practices for big data-driven healthcare innovations conducted by profit-non-profit partnerships - a quantitative prioritization. International Journal of Healthcare Management, 11(3), 171-181.

van Buuren J., & Wong, A. (2016). Debate on public audit oversight enforcement: It is all about procedural justice? Maandblad Voor Accountancy en Bedrijfseconomie, 90(9), 352-356.

Cramer, A. O. J., van Ravenzwaaij, D., Matzke, D., Steingroever, H., Wetzels, R., Grasman, R. P. P. P., Waldorp, L.,J., & Wagenmakers, E.-J. (2016). Hidden multiplicity in exploratory multiway ANOVA: Prevalence and remedies. Psychonomic Bulletin & Review, 23, 640-647.

Steingroever, H., Wetzels, R., & Wagenmakers, E.-J. (2016). Bayes factors for reinforcement-learning models of the Iowa gambling task. Decision, 3(2), 115-131.

Wetzels, R., Tutschkow, T., Dolan, C. V., van der Sluis, S., Dulith, G., & Wagenmakers, E.-J. (2016). A Bayesian test for the hot hand phenomenon. Journal of Mathematical Psychology, 72, 200-209.

van Buuren, J. (2015). Controlekwaliteit blijft een belevenis. Maandblad Voor Accountancy en Bedrijfseconomie, 89(3), 67-76.

Litjens, R., van Buuren, J. and Vergoossen, R. (2015). Addressing information needs to reduce the audit expectation gap: Evidence from Dutch bankers, audited companies and auditors. International Journal of Auditing, 19, 267-281.

Nuijten, M.B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E.-J. (2015). A default Bayesian hypothesis test for mediation. Behavioral Resesearch Methods, 47, 85-97.

Steingroever, H., Fridberg, D. J., Horstmann, A., Kjome, K. L., Kumari, V., Lane, S. D., Maia, T. V., McClelland, J. L., Pachur, T., Premkumar, P., Stout, J. C., Wetzels, R., Wood, S., Worthy, D. A., & Wagenmakers, E.-J. (2015). Data from 617 healthy participants performing the Iowa Gambling Task: A "many labs" collaboration. Journal of Open Psychology Data, 3(1).

Steingroever, H., Wetzels, R., & Wagenmakers, E.-J. (2015). Ŵ=.2, â=.8, ĉ=.6: So what? On the meaning of parameter estimates from reinforcement-learning models. Decision, 2(3), 228-235.

Wetzels, R., van Ravenzwaaij, D. and Wagenmakers, E.-J. (2015). Bayesian Analysis. In The Encyclopedia of Clinical Psychology. John Wiley & Sons.

Bartletma, A., Lee, M. D., Wetzels, R., & Vanpaemel, W. (2014). A Bayesian hierarchical mixture approach to individual differences: Case studies in selective attention and representation in category learning. Journal of Mathematical Psychology, 59, 132-150.

van Buuren, J., Koch, C., van Nieuw Amerongen, N., & Wright, A. M. (2014). The use of business risk audit perspectives by non-big 4 audit firms. Auditing: A Journal of Practice & Theory, 33(3), 105–128.

Huizenga, H., Van Duijvenvoorde, A., Van Ravenzwaaij, D., Wetzels, R., & Jansen, B. (2014). Is the unconscious, if it exists, a superior decision maker? Behavioral and Brain Sciences, 37(1), 32-33.

Steingroever, H., Wetzels, R., & Wagenmakers, E.-J. (2014). Absolute performance of reinforcement-learning models for the Iowa Gambling Task. Decision, 1(3), 161-183.

Wetzels, R., Lee, M.D., & Wagenmakers, E.-J. (2014). Comparing Gaussian Means. In Bayesian Cognitive Modeling: A Practical Course. Cambridge University Press.

Wetzels, R., Lee, M.D., & Wagenmakers, E.-J. (2014). The Generalized Contexts Model. In Bayesian Cognitive Modeling: A Practical Course. Cambridge University Press.

Steingroever, H., Wetzels, R., Horstmann, A., Neumann, J., & Wagenmakers, E.-J. (2013). Performance of healthy participants on the Iowa Gambling Task. Psychological Assessment, 25(1), 180-193.

Steingroever, H., Wetzels, R., & Wagenmakers, E.-J. (2013). A comparison of reinforcement learning models for the Iowa Gambling Task using parameter space partitioning. The Journal of Problem Solving, 5(2).

Steingroever H., Wetzels R. and Wagenmakers E.-J. (2013). Validating the PVL-Delta model for the Iowa gambling task. Frontiers in Psychology, 4, 898.

de Swart, J. J. B., Wille, J., & Majoor, B. (2013). Het 'push left'-principe als motor van data analytics in de accountantscontrole. Maandblad Voor Accountancy en Bedrijfseconomie, 87(10), 425-433.

Dyjas, O., Grasman, R. P. P. P., Wetzels R., van der Maas, H. L. J., & Wagenmakers, E.-J. (2012). What's in a name: A Bayesian hierarchical analysis of the name-letter effect Frontiers in Psychology, 3, 334.

Huizenga, H. M., Wetzels, R., van Ravenzwaaij, D., & Wagenmakers, E.-J. (2012). Four empirical tests of unconscious thought theory. Organizational Behavior and Human Decision Processes, 117(2), 332-340.

Wagenmakers, E.-J., Wetzels, R., Borsboom, D., van der Maas, H. L. J., & Kievit, R. A. (2012). An agenda for purely confirmatory research. Perspectives on Psychological Science, 7(6), 632-638.

Wetzels, R. M. (2012). Bayesian Model Selection with Applications in Social Science. PhD Thesis. Universiteit van Amsterdam, Amsterdam.

Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E.-J. (2012). A default Bayesian hypothesis test for ANOVA designs. The American Statistician, 66, 104-111.

Wetzels, R., & Wagenmakers, E.-J. (2012). A default Bayesian hypothesis test for correlations and partial correlations. Psychonomic Bulletin & Review, 19, 1057-1064.

van Buuren, J. & van Nieuw Amerongen, N. (2011). Business risk auditing in de 21e eeuw, uniform toepasbaar?! Maandblad Voor Accountancy en Bedrijfseconomie, 85(10), 512-520.

Wagenmakers, E.-J., Wetzels, R., Borsboom, D., Kievit, R., & van der Maas, H. (2011). Yes, psychologists must change the way they analyze their data: Clarifications for Bem, Utts, and Johnson (2011). PsyArXiv.

Wagenmakers, E.-J., Borsboom, D., Kievit, R., & van der Maas, H. (2011). Why psychologists must change the way they analyze their data: the case of psi: Comment on Bem (2011). ournal of Personality and Social Psychology, 100(3), 426-432.

Wetzels, R., Matzke, D., Lee, M. D., Rouder, J. N., Iverson, G. J., & Wagenmakers, E.-J. (2011). Statistical evidence in experimental psychology: An empirical comparison using 855 t tests. Perspectives on Psychological Science, 6(3), 291-298.

Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E.-J. (2010). An encompassing prior generalization of the Savage-Dickey density ratio. Computational Statistics & Data Analysis, 54(9), 2094-2102.

Wetzels, R., Lee, M.D., & Wagenmakers, E.-J. (2010). Bayesian inference using WBDev: A tutorial for social scientists. Behavior Research Methods, 42, 884-897.

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(1), 14-27.

van Buuren, J. (2009). On the Nature of Auditing: The Audit Partner Effect: Research on the Effect of Individual Audit Partners on Audit Quality and the Information Dynamics of Accounting Data. PhD Thesis. Nyenrode Business Universiteit, Breukelen.

Wetzels, R., Raaijmakers, J. G. W., Jakab, E., & Wagenmakers, E-.J. (2009). How to quantify support for and against the null hypothesis: A flexible WinBUGS implementation of a default Bayesian t test. Psychonomic Bulletin & Review, 16, 752-760.

Stortelder, W. J. H., de Swart, J. J. B. & Pínter, J. (2001). Finding elliptic Fekete points sets: two numerical solution approaches. Journal of Computational and Applied Mathematics, 130(1/2), 205-216.

van der Houwen, P. J., Messina, E., & de Swart, J. J. B. (1999). Parallel Störmer-Cowell methods for high-precision orbit computations. Applied Numerical Mathematics, 31(3), 353-374.

Hoffmann, W., & de Swart, J. J. B. (1997). Approximating Runge-Kutta matrices by triangular matrices. Bit Numer Math, 37, 346-354.

van der Houwen, P. J., & de Swart, J. J. B. (1997). Parallel linear system solvers for Runge-Kutta methods. Advances in Computational Mathematics, 7, 157-181.

van der Houwen, P. J., & de Swart, J. J. B. (1997). Triangularly Implicit Iteration Methods for ODE-IVP Solvers. SIAM Journal on Scientific Computing.

Messina, E., de Swart, J. J. B., & van der Veen, W., A. (1997). Parallel iterative linear solvers for multistep Runge-Kutta methods. Journal of Computational and Applied Mathematics, 85(1), 145-167.

de Swart, J. J. B. (1997). A simple ODE solver based on 2-stage Radau IIA. Journal of Computational and Applied Mathematics, 84(2), 277-280.

de Swart, J. J. B., & Söderlind, G. (1997). On the construction of error estimators for implicit Runge-Kutta methods. Journal of Computational and Applied Mathematics, 86(2), 347-358.

van der Houwen, P. J., Sommeijer, B. P., & de Swart, J. J. B. (1996). Parallel predictor-corrector methods. Journal of Computational and Applied Mathematics, 66(1/2), 53-71.

de Swart, J. J. B., & Blom, J. G. (1996). Experiences with sparse matrix solvers in parallel ODE software. Computers & Mathematics with Applications, 31(9), 43-55.

de Swart, J. J. B. (1995). Efficient parallel predictor-corrector methods. Applied Numerical Mathematics, 18(1/3), 387-396.

van der Veen, W. A., de Swart, J. J. B., & van der Houwen, P. J. (1995). Convergence aspects of step-parallel iteration of Runge-Kutta methods. Applied Numerical Mathematics, 18(1/3), 397-411.