papers

Most of my publications can be found at Google Scholar. Below, work in progress is listed first; let me know if you want more information about any of these projects.

Work in progress

  • Godmann, H. R., Haaf, J. M., Visser, I., Szymanik, J., & Sarafoglou, A. (2026). Toward a Principled Bayesian Workflow in Semantics and Pragmatics: A Tutorial . [preprint]
  • Johnson, T., Sarafoglou, A., Haaf, J. M., Visser, I., & Szymanik, J. (2026). Modeling Scalar Categorization: Comparing Threshold-Based and Prototype-Based Representations . [preprint]
  • Visser, I., Geambașu, A., Kachergis, G., Oliveira, C. M., Rocha-Hidalgo, J., Zettersten, M., Ahamat, T. M., Alessandroni, N., Althaus, N., Arunachalam, S., Aussems, S., Axelsson, E., Aydin, Z., Baumgartner, H. A., Bergmann, C., Bettoni, R., Black, A., Bulf, H., Byers-Heinlein, K., Capparini, C., Carroll, L., Carstensen, C. A., Cebulla, R., Chen, X., Chladkova, K., Colavolpe, B., Constantine, R., Cortes, E. E., Doyle, F. L., Exner, A., Forbes, S. H., Franchin, L., Geraci, A., Gervain, J., Gonzalez-Gomez, N., Hagelund, S., Hannon, E., Havron, N., Jaffe-Dax, S., Johnson, S., Jędryczka, W., Kartushina, N., Kline Struhl, M., Koleini, A., Kona, A., Kong, S., Kosie, J. E., Kučerová, M., Kynclova, K., Leslie, J., Lew-Williams, C., Li, S. W. Y., livne, r., Marklund, E., Mayor, J., Misiak, M., Moreau, D., Mueller, J. L., Muhinyi, A., Quinn, A., Raijmakers, M. E. J., Rosslund, A., Schwarz, I., Shinskey, J. L., Shukla, M., Sirois, S., Sorokowski, P., Sowan, B., Tauzin, T., Tsui, A., Turconi, M., Urizar, R., Wagner, L., Wermelinger, S., Westermann, G., Weyers, I., Yuan, L., Zaharieva, M. S., Zamuner, T. S., Zapiór, B., zasso, s., Zhou, G., Soderstrom, M., & Levelt, C. (2026). ManyBabies 3: A Multi-Lab Study of Infant Algebraic Rule Learning . [preprint]
  • Zaharieva, M., Collonesi, C., & Visser, I. (2026). Endogenous Attention, Emotion Regulation, Feeding, and Sleep in 3- to 13-Month-Old Infants. [in preparation]
  • Maat, S. C., Dreuning, K. M., Janssen, S. J., Visser, I., Hunnius, S., Stevens, M. F., de Graaff, J. C., van Heurn, L. E., Königs, M., Oosterlaan, J., & Derikx, J. P. (2026). General anesthesia exposure and neurocognitive outcome in infants. [under review]
  • Alessandroni, N., Miller, R., Altschul, D., Barrett, L. P., Bazhydai, M., Elsherif, M., Espinosa, J., Gjoneska, B., Héjja-Brichard, Y., Mazza, V., Paukner, A., Pronizius, E., Proulx, M., Qadri, M., Reilly, O., Schwing, R., Sebastián-Enesco, C., Šlipogor, V., de Sousa, A., Visser, I., et al. (2025). Flexible behavior or flexible methods? A cross-taxon review of experimental designs in reversal learning . [preprint: https://doi.org/10.31234/osf.io/mvche_v4]
  • Schuwerk, T., Kampis, D., Alessandroni, N., Altvater-Mackensen, N., Arias-Trejo, N., Axelsson, E. L., Baillargeon, R., Baumann, A., Bernard, C., Biro, S., Blankenship, T. L., Blomberg, I., Bohn, M., Bradford, E. E. F., Byers-Heinlein, K., Canudas Grabolosa, I., Chen, E. M., Chen, X., Corbit, J., Dörrenberg, S., Fisher, C., Forbes, S. H., Franchin, L., Fulcher, T., Geraci, A., Gonzalez-Gomez, N., Grohmann, P., Grosse Wiesmann, C., Hamlin, J. K., Haun, D., Havron, N., Hepach, R., Hermansen, T. K., Hernik, M., Huemer, M., Hunnius, S., Hyde, D. C., Jaffe-Dax, S., Jakobsen, K. V., Jankiewicz, G., Jędryczka, W., Kartushina, N., Kfir, C., Khalaila, M., Kingo, O. S., Klau, M. M., Koleini, A., Kona, A., Kong, S. P., Kosakowski, H. L., Kovács, Á. M., Krämer, A., Krief, J. L., Krøjgaard, P., Kulke, L., Lee, C. Y., Legg, E. W., Leung, T. S., Lew-Williams, C., Li, Y., Liszkowski, U., Liu, L., Liu, Y., Mackiel, A., Mahowald, K., Marx, M., Mascaro, O., Matetovici, M., Mayer, M., Mayor, J., Meristo, M., Meyer, M., Misiak, M., Moreau, D., Hay Mar Myat Kyaw, Nistor, A. A., Perner, J., Peykarjou, S., Pham, Q. A., Poulin-Dubois, D., Powell, L. J., Prein, J. C., Priewasser, B., Proft, M., Quinn, A. A., Raz, G., Reschke, P. J., Ross, J., Rosslund, A., Rothmaler, K., Šarić, P., Saxe, R., Schlegelmilch, K., Schneider, D., Schreiner, M. S., Schuhmann, V., Scifo, L., Shapiro, L., Simpson, E. A., Smith, L., Sonne, T., Sorokowski, P., Southgate, V., Steffan, A., Su, Y., Surian, L., Tan, A. W. M., Tebbe, A., Tsui, A. S. M., Visser, I., Wang, Y., Wertz, A. E., Westermann, G., Woodward, A. L., Wu, Y., Yu, Y., Yuen, F., Yuile, A. R., Zeng, Z., Zettersten, M., Zimmer, L., Frank, M. C., & Rakoczy, H. (2025). Action anticipation based on an agent’s epistemic state in toddlers and adults . [preprint]
  • Wassink-de Stigter, R., Jansen, R., Deen, M., Visser, I., Simons, I., & Soenen, S. (2025). Subtypes of Families with Multiple and Complex Problems within Integrated Specialized Family-Focused Mental Health Care. Journal of Family Issues. [under review]
  • van Kordelaar, J., Visser, I., van Vliet, E., & van Weijen, D. (2025). Rubric use in writing assessment: relations between assessors’ experience and satisfaction. [under review]
  • Zaharieva, M., Collonesi, C., & Visser, I. (2025). Growing emotion and attention regulation: a toolbox for studying self-regulation in infancy. [in preparation]
  • Exner, A., Bettoni, R., Cantiani, C., Koleini, A., Oliveira, C. M., Thompson, A., Visser, I., & Zettersten, M. (2024). The relationship between rule learning in infancy (5-12 months) and language skills at 24-30 months.
  • Exner, A., Mayor, J., Moreau, D., Oliveira, C. M., Soderstrom, M., Tauzin, T., Visser, I., Weyers, I., & Zettersten, M. (2023). Assessing test-retest reliability of rule learning measures in infants .
  • Franse, R., van Schijndel, T. J., Visser, I., & Raijmakers, M. (2023). Children’s understanding of floating and sinking: Predictions and explanations tell different stories . [preprint: https://doi.org/10.31219/osf.io/h5mcs]
  • Kosie, J., Zettersten, M., Abu-Zhaya, R., Amso, D., Babineau, M., Baumgartne, H., Belia, M., Benavides, S., Bergmann, C., Berteletti, I., et al. (2023). ManyBabies 5: A large-scale investigation of the proposed shift from familiarity preference to novelty preference in infant looking time . [stage 1 registered report]
  • Kucharský, Š., Raijmakers, M., & Visser, I. (2023). Strategy classification in economic games using eye-movement data. [in preparation]
  • Schaaf, J., Huizenga, H., Visser, I., & Jepma, M. (2023). Context valence affects learning mechanisms and confidence, but not learning, in adolescents.
  • Zaharieva, M., Kucharský, Š., & Visser, I. (2023). Habituation, Part I. Design Choices in the Infant Habituation Paradigm: A Pre-registered Crowd-Sourced Systematic Review and Meta-Analysis . [stage 1 registered report]
  • Kucharský, Š., Houtkoop, B. L., & Visser, I. (2020). Code Sharing in Psychological Methods and Statistics: An Overview and Associations with Conventional and Alternative Research Metrics . [preprint: https://doi.org/10.31219/osf.io/daews]
  • Visser, I. (2014). Why reproducible reporting?.

Journal articles

2026

  • Vaidis, D. C., Miranda, J. F., Buchanan, E. M., Yang, Y. F., Kowal, M., Schmidt, K., Topor, M., Misiak, M., Miller, R., Protzko, J., Gjoneska, B., Miller, J. K., Exner, A., Azevedo, F., Paruzel-Czachura, M., Mushtaq, F., Oliveira, C., Wagge, J. R., De Moor, D., Mede, N. G., Altschul, D. M., Pavlov, Y. G., Seetahul, Y., Boucher, L., Doell, K. C., Visser, I., Elsherif, M. M., & Pronizius, E. (2026). The Advantage of Big Team Science: Lessons Learned from Cognitive Science. Collabra: Psychology, 12(1), 160129 .
  • Korthals, L., Akrong, E., Geller, G., Rosenbusch, H., Grasman, R., & Visser, I. (2026). Towards Reliable LLM Grading Through Self-Consistency and Selective Human Review: Higher Accuracy, Less Work. Machine Learning and Knowledge Extraction, 8(3), 74 .
  • McMillan, B., Baumgartner, H., Bergmann, C., Frank, M. C., Hamlin, J. K., Kampis, D., Kline Struhl, M., Ko, E., Kosie, J., Lew-Williams, C., Lucca, K., Schuwerk, T., Soderstrom, M., Visser, I., Yuen, F., Zettersten, M., & Byers-Heinlein, K. (2026). What 5000 Babies Can Tell Us About Developing Minds and How to Study Them. Communications Psychology.

2025

  • Sarafoglou, A., Giacobello, A., Godmann, H., Johnson, T., Visser, I., Haaf, J. M., & Szymanik, J. (2025). Are semantic representations stable? A Bayesian framework .
  • Alessandroni, N., Altschul, D., Baumgartner, H., Bazhydai, M., Brosnan, S., Byers-Heinlein, K., Call, J., Chittka, L., Elsherif, M., Espinosa, J., Freeman, M., Gjoneska, B., Güntürkün, O., Huber, L., Krasheninnikova, A., Mazza, V., Miller, R., Moreau, D., Nawroth, C., Pronizius, E., Ruiz-Fernández, S., Schwing, R., Šlipogor, V., Visser, I., Vonk, J., Yeager, J., Zettersten, M., & Prétôt, L. (2025). Challenges and promises of big team comparative cognition. Nature Human Behaviour, 9(2), 240–242 .
  • Lucca, K., Capelier-Mourguy, A., Cirelli, L., Byers-Heinlein, K., Dal Ben, R., Frank, M. C., Henderson, A. M., Kominsky, J. F., Liberman, Z., Margoni, F., et al. (2025). Infants’ Social Evaluation of Helpers and Hinderers: A Large-Scale, Multi-Lab, Coordinated Replication Study. Developmental Science, 28(1) .
  • Speekenbrink, M. & Visser, I. (2025). State-Dependent Missingness in Hidden Markov Models, with an Application to Drop-Out in a Clinical Trial. Psychometrika, 90(2), 476–507 .

2024

  • Sarafoglou, A., Giacobello, A., Godmann, H., Johnson, T., Visser, I., Haaf, J. M., & Szymanik, J. (2024). A Bayesian Framework To Study Individual Differences In Semantic Representations .
  • Zaharieva, M. S., Salvadori, E. A., Messinger, D. S., Visser, I., & Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sample of 4-and 8-month-olds: Baby FaceReader 9 and manual coding of affective expressions. Behavior Research Methods, 56(6), 5709–5731 .
  • Alessandroni, N., Altschul, D., Bazhydai, M., Byers-Heinlein, K., Elsherif, M., Gjoneska, B., Huber, L., Mazza, V., Miller, R., Nawroth, C., Pronizius, E., Qadri, M., Šlipogor, V., Soderstrom, M., Stevens, J., Visser, I., Williams, M., Zettersten, M., & Prétôt, L. (2024). Comparative Cognition Needs Big Team Science: How Large-Scale Collaborations Will Unlock the Future of the Field. Comparative Cognition and Behavior Reviews, 19, 67–72 .
  • Kucharský, Š., Zaharieva, M., Raijmakers, M., & Visser, I. (2024). Habituation, part II. Rethinking the habituation paradigm. Infant and Child Development, 33(1), e2383 .
  • Hoogeveen, S., Borsboom, D., Kucharský, Š., Marsman, M., Molenaar, D., de Ron, J., Sekulovski, N., Visser, I., van Elk, M., & Wagenmakers, E. (2024). Prevalence, patterns and predictors of paranormal beliefs in The Netherlands: a several-analysts approach. Royal Society Open Science, 11(9), 240049 .
  • Schaaf, J. V., Johansson, A., Visser, I., & Huizenga, H. M. (2024). What’s in a name: The role of verbalization in reinforcement learning. Psychonomic Bulletin and Review, 31(6), 2746–2757 .

2023

  • Visser, I., Kucharský, Š., Levelt, C., Stefan, A. M., Wagenmakers, E., & Oakes, L. (2023). Bayesian sample size planning for developmental studies. Infant and Child Development, 33(1), e2412 .
  • Wesarg-Menzel, C., Ebbes, R., Hensums, M., Wagemaker, E., Zaharieva, M., Staaks, J., van den Akker, A., Visser, I., Hoeve, M., Brummelman, E., Dekkers, T., Schuitema, J., Larsen, H., Colonnesi, C., Jansen, B., Overbeek, G., Huizenga, H., & Wiers, R. (2023). Development and socialization of self-regulation from infancy to adolescence: A meta-review differentiating between self-regulatory abilities, goals, and motivation. Developmental Review, 69, 101090 .
  • Lichtenberg, L., Visser, I., & Raijmakers, M. (2023). Latent Markov Models to Test the Strategy Use of 3-Year-Olds in a Rule-Based Feedback-Learning Task. Multivariate Behavioral Research, 59(6), 1123–1136 .
  • Spit, S., Geambașu, A., Renswoude, D. v., Blom, E., Fikkert, P., Hunnius, S., Junge, C., Verhagen, J., Visser, I., Wijnen, F., & Levelt, C. C. (2023). Robustness of the cognitive gains in 7-month-old bilingual infants: A close multi-center replication of Kov'acs and Mehler (2009). Developmental Science, 26(6), e13377 .
  • Geambașu, A., Spit, S., van Renswoude, D., Blom, E., Fikkert, P. J., Hunnius, S., Junge, C. C., Verhagen, J., Visser, I., Wijnen, F., & Levelt, C. C. (2023). Robustness of the rule-learning effect in 7-month-old infants: A close, multicenter replication of Marcus et al.(1999). Developmental Science, 26(1), e13244 .

2022

  • Schaaf, J. V., Xu, B., Jepma, M., Visser, I., & Huizenga, H. M. (2022). (Mal) Adaptive Learning After Switches Between Object-Based and Rule-Based Environments. Computational Brain & Behavior, 5(2), 157–167 .
  • Lüken, M., Kucharský, Š., & Visser, I. (2022). Characterising eye movement events with an unsupervised hidden markov model. Journal of Eye Movement Research, 15(1) .
  • Jepma, M., Schaaf, J. V., Visser, I., & Huizenga, H. M. (2022). Impaired learning to dissociate advantageous and disadvantageous risky choices in adolescents. Scientific Reports, 12(1), 1–14 .
  • Visser, I., Bergmann, C., Byers-Heinlein, K., Dal Ben, R., Duch, W., Forbes, S., Franchin, L., Frank, M., Geraci, A., Hamlin, J. K., et al. (2022). Improving the generalizability of infant psychological research: The ManyBabies model. Behavioral and Brain Sciences, 45 .
  • Visser, I. (2022). No data left behind. Infant and Child Development, 31(5), e2339 .

2021

  • Jepma, M., Schaaf, J. V., Visser, I., & Huizenga, H. M. (2021). Effects of advice on experienced-based learning in adolescents and adults. Journal of Experimental Child Psychology, 211, 105230 .
  • Kucharský, Š., Tran, N., Veldkamp, K., Raijmakers, M., & Visser, I. (2021). Hidden Markov models of evidence accumulation in speeded decision tasks. Computational Brain and Behavior, 4(4), 416–441 .
  • Kuijpers, R. E., Visser, I., & Molenaar, D. (2021). Testing the within-state distribution in mixture models for responses and response times. Journal of Educational and Behavioral Statistics, 46(3), 348–373 .
  • Byers-Heinlein, K., Tsui, R. K., van Renswoude, D., Black, A., Barr, R., Brown, A., Colomer, M., Durrant, S., Gonzalez-Gomez, N., Hay, J., Hernik, M., Jartó, M., Kovács, Á., Laoun-Rubenstein, A., Lew-Williams, C., Liszkowski, U., Liu, L., Noble, C., Potter, C., Rocha-Hidalgo, J., Sebastian-Galles, N., Soderstrom, M., Visser, I., Waddell, C., Wermelinger, S., & Singh, L. (2021). The development of gaze following in monolingual and bilingual infants: A multi-laboratory study. Infancy, 26(1), 4–38 .
  • Kucharský, Š., van Renswoude, D., Raijmakers, M., & Visser, I. (2021). WALD-EM: Wald accumulation for locations and durations of eye movements.. Psychological Review, 128(4), 667 .

2020

  • van Bers, B. M., van Schijndel, T. J., Visser, I., & Raijmakers, M. E. (2020). Cognitive flexibility training has direct and near transfer effects, but no far transfer effects, in preschoolers. Journal of Experimental Child Psychology, 193, 104809 .
  • Kucharský, Š., Visser, I., Truțescu, G., Laurence, P. G., Zaharieva, M., & Raijmakers, M. E. (2020). Cognitive strategies revealed by clustering eye movement transitions. Journal of Eye Movement Research, 13(1) .
  • van Renswoude, D. R., Raijmakers, M. E., & Visser, I. (2020). Looking (for) patterns: Similarities and differences between infant and adult free scene-viewing patterns. Journal of Eye Movement Research, 13(1) .
  • Mulder, K., Klugkist, I., van Renswoude, D., & Visser, I. (2020). Mixtures of peaked power Batschelet distributions for circular data with application to saccade directions. Journal of Mathematical Psychology, 95, 102309 .
  • Jepma, M., Schaaf, J. V., Visser, I., & Huizenga, H. M. (2020). Uncertainty-driven regulation of learning and exploration in adolescents: A computational account. PLoS Computational Biology, 16(9), e1008276 .

2019

  • Schaaf, J. V., Jepma, M., Visser, I., & Huizenga, H. M. (2019). A hierarchical Bayesian approach to assess learning and guessing strategies in reinforcement learning. Journal of Mathematical Psychology, 93, 102276 .
  • van Renswoude, D. R., van den Berg, L., Raijmakers, M. E., & Visser, I. (2019). Infants’ center bias in free viewing of real-world scenes. Vision Research, 154, 44–53 .
  • Bayarri, M., Berger, J. O., Jang, W., Ray, S., Pericchi, L. R., & Visser, I. (2019). Prior-based Bayesian information criterion. Statistical Theory and Related Fields, 3(1), 2–13 .
  • van Renswoude, D. R., Visser, I., Raijmakers, M. E., Tsang, T., & Johnson, S. P. (2019). Real-world scene perception in infants: What factors guide attention allocation?. Infancy, 24(5), 693–717 .
  • Berger, J., Jang, W., Ray, S., Rericchi, L. R., & Visser, I. (2019). Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser. Statistical Theory and Related Fields, 3(1), 37–39 .

2018

  • Hofman, A. D., Visser, I., Jansen, B. R., Marsman, M., & van der Maas, H. L. (2018). Fast and slow strategies in multiplication. Learning and Individual Differences, 68, 30–40 .
  • van Renswoude, D. R., Raijmakers, M. E., Koornneef, A., Johnson, S. P., Hunnius, S., & Visser, I. (2018). Gazepath: An eye-tracking analysis tool that accounts for individual differences and data quality. Behavior Research Methods, 50(2), 834–852 .
  • van Schijndel, T. J., Huijpen, K., Visser, I., & Raijmakers, M. E. (2018). Investigating the development of causal inference by studying variability in 2-to 5-year-olds’ behavior. PLoS ONE, 13(4), e0195019 .
  • Dutilh, G., Annis, J., Brown, S., Cassey, P., Evans, N., Grasman, R., Hawkins, G., Heathcote, A., Holmes, W., Krypotos, A., Kupitz, C., Leite, F., Lerche, V., Lin, Y., Logan, G., Palmeri, T., Starns, J., Trueblood, J., van Maanen, L., van Ravenzwaaij, D., Vandekerckhove, J., Visser, I., Voss, A., White, C., Wiecki, T., Rieskamp, J., & Donkin, C. (2018). The quality of response time data inference: A blinded, collaborative assessment of the validity of cognitive models. Psychonomic Bulletin & Review, 26(4), 1051–1069 .

2017

  • Molenaar, D., Visser, I., et al. (2017). Cognitive and psychometric modelling of responses and response times. British Journal of Mathematical & Statistical Psychology, 70(2), 185–186 .
  • Visser, I. & Poessé, R. (2017). Parameter recovery, bias and standard errors in the linear ballistic accumulator model. British Journal of Mathematical and Statistical Psychology, 70(2), 280–296 .

2016

  • Blakey, E., Visser, I., & Carroll, D. J. (2016). Different executive functions support different kinds of cognitive flexibility: Evidence from 2-, 3-, and 4-year-olds. Child Development, 87(2), 513–526 .
  • van Renswoude, D., Johnson, S., Raijmakers, M., & Visser, I. (2016). Do infants have the horizontal bias?. Infant Behavior and Development, 44, 38–48 .
  • Jansen, B. R., Hofman, A. D., Savi, A., Visser, I., & van der Maas, H. L. (2016). Self-adapting the success rate when practicing math. Learning and Individual Differences, 51, 1–10 .
  • Souverein, F. A., Ward, C. L., Visser, I., & Burton, P. (2016). Serious, violent young offenders in South Africa: Are they life-course persistent offenders?. Journal of Interpersonal Violence, 31(10), 1859–1882 .

2015

  • Hosenfeld, B., Bos, E. H., Wardenaar, K. J., Conradi, H. J., van der Maas, H. L., Visser, I., & de Jonge, P. (2015). Major depressive disorder as a nonlinear dynamic system: bimodality in the frequency distribution of depressive symptoms over time. Bmc psychiatry, 15(1), 1–9 .
  • van Schijndel, T. J., Visser, I., van Bers, B. M., & Raijmakers, M. E. (2015). Preschoolers perform more informative experiments after observing theory-violating evidence. Journal of experimental child psychology, 131, 104–119 .
  • Hofman, A. D., Visser, I., Jansen, B. R., & van der Maas, H. L. (2015). The balance-scale task revisited: A comparison of statistical models for rule-based and information-integration theories of proportional reasoning. PLoS One, 10(10), e0136449 .

2014

  • Andersen, L. M., Visser, I., Crone, E. A., Koolschijn, P., & Raijmakers, M. E. (2014). Cognitive strategy use as an index of developmental differences in neural responses to feedback.. Developmental psychology, 50(12), 2686 .
  • Visser, I. & Speekenbrink, M. (2014). Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates. Test, 23, 478–483 .
  • Raijmakers, M. E., Schmittmann, V. D., & Visser, I. (2014). Costs and benefits of automatization in category learning of ill-defined rules. Cognitive psychology, 69, 1–24 .
  • van Bers, B. M., Visser, I., & Raijmakers, M. (2014). Preschoolers learn to switch with causally related feedback. Journal of Experimental Child Psychology, 126, 91–102 .
  • Van Bers, B., Visser, I., & Raijmakers, M. (2014). The distinctive effects of exogenous factors on preschoolers’ DCCS performance. Manuscript submitted for publication.

2013

  • Ihrke, M., Behrendt, J., Schrobsdorff, H., Visser, I., & Hasselhorn, M. (2013). Negative priming persists in the absence of response-retrieval. Experimental Psychology, 60(1), 12-21 .

2012

  • Visser, I. & Raijmakers, M. E. (2012). Developing representations of compound stimuli. Frontiers in psychology, 3, 73 .

2011

  • Dutilh, G., Wagenmakers, E., Visser, I., & van der Maas, H. L. (2011). A phase transition model for the speed-accuracy trade-off in response time experiments. Cognitive Science, 35(2), 211–250 .
  • Visser, I. (2011). Seven things to remember about hidden Markov models: A tutorial on Markovian models for time series. Journal of Mathematical Psychology, 55(6), 403–415 .
  • Huizenga, H. M., Visser, I., & Dolan, C. V. (2011). Testing overall and moderator effects in random effects meta-regression. British Journal of Mathematical and Statistical Psychology, 64(1), 1–19 .
  • van Bers, B. M., Visser, I., van Schijndel, T. J., Mandell, D. J., & Raijmakers, M. E. (2011). The dynamics of development on the Dimensional Change Card Sorting task. Developmental Science, 14(5), 960–971 .

2010

  • van Duijvenvoorde, A. C., Jansen, B. R., Visser, I., & Huizenga, H. M. (2010). Affective and cognitive decision-making in adolescents. Developmental neuropsychology, 35(5), 539–554 .
  • Visser, I. (2010). Review of: W. Zucchini, IL MacDonald (2009) Hidden Markov models for time series: an introduction using R.. Journal of Mathematical Psychology, 54(6), 509–511 .
  • Pronk, T. & Visser, I. (2010). The role of reversal frequency in learning noisy second order conditional sequences. Consciousness and cognition, 19(2), 627–635 .
  • Visser, I. & Speekenbrink, M. (2010). depmixS4: An R Package for Hidden Markov Models. Journal of Statistical Software, 36(7), 1–21 .

2009

  • Visser, I., Raijmakers, M. E., & van der Maas, H. L. (2009). Hidden Markov models for individual time series. Dynamic process methodology in the social and developmental sciences, 269–289 .
  • Visser, I., Raijmakers, M. E., & Pothos, E. M. (2009). Individual strategies in artificial grammar learning. The American journal of psychology, 122(3), 293–307 .

2008

  • Visser, I., et al. (2008). Review of: J. Rissanen (2007) Information and complexity in statistical modeling. Kwantitatieve Methoden, 2007, 1–2 .
  • Borsboom, D. & Visser, I. (2008). Semantic cognition or data mining?. Behavioral and Brain Sciences, 31(6), 714–715 .

2007

  • Visser, I., Raijmakers, M. E., & Molenaar, P. C. (2007). Characterizing sequence knowledge using online measures and hidden Markov models. Memory & Cognition, 35(6), 1502–1517 .
  • Jansen, B. R., Raijmakers, M. E., & Visser, I. (2007). Rule transition on the balance scale task: a case study in belief change. Synthese, 155, 211–236 .
  • Visser, I. (2007). depmix: An R-package for fitting mixture models on mixed multivariate data with Markov dependencies. R-package manual, 39, 65 .

2006

  • Schmittmann, V. D., Visser, I., & Raijmakers, M. E. (2006). Multiple learning modes in the development of performance on a rule-based category-learning task. Neuropsychologia, 44(11), 2079–2091 .

2005

  • Van Der Maas, H. L., Raijmakers, M. E., & Visser, I. (2005). Inferring the structure of latent class models using a genetic algorithm. Behavior research methods, 37, 340–352 .

2002

  • Visser, I., Raijmakers, M. E., & Molenaar, P. (2002). Fitting hidden Markov models to psychological data. Scientific Programming, 10(3), 185–199 .

2000

  • Visser, I., Raijmakers, M. E., & Molenaar, P. (2000). Confidence intervals for hidden Markov model parameters. British journal of mathematical and statistical psychology, 53(2), 317–327 .
  • Visser, I. (2000). Hidden Markov model interpretations of neural networks. Behavioral and Brain Sciences, 23(4), 494–495 .

Book chapters

  • Korthals, L., Rosenbusch, H., Grasman, R., & Visser, I. (2025). Grading University Students with LLMs: Performance and Acceptance of a Canvas-Based Automation. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED .
  • Visser, I. (2025). Hidden Markov Models. Open Encyclopedia of Cognitive Science .
  • Visser, I. & Speekenbrink, M. (2022). Hidden Markov Models. Mixture and Hidden Markov Models with R .
  • Visser, I., Schmittmann, V. D., & Raijmakers, M. E. (2017). Markov process models for discrimination learning. Longitudinal models in the behavioral and related sciences .
  • Visser, I. (2011). Methodological solipsism. The Cambridge encyclopedia of language sciences.
  • Visser, I., Jansen, B. R., & Speekenbrink, M. (2010). A framework for discrete change.. Individual pathways of change: statistical models for analyzing learning and development .

Conference proceedings

  • Johnson, T., Sarafoglou, A., Haaf, J. M., Visser, I., & Szymanik, J. (2024). Comparing the Threshold and Prototype Model for Gradable Adjectives. Proceedings of the Annual Meeting of the Cognitive Science Society .
  • Frank, M., Kunda, N., Lavechin, M., Oudeyer, P., Saxe, R., de Seyssel, M., & Visser, I. (2023). 4.3 Group 2.1: Embodied Intention Prediction Challenge. Developmental Machine Learning: From Human Learning to Machines and Back (Dagstuhl Seminar 22422) .
  • Visser, I. & Speekenbrink, M. (2014). It’s a Catastrophe! Testing dynamics between competing cognitive states using mixture and hidden Markov models. CogSci 2014 .
  • Nivard, M., van der Sluis, S., Franic, S., Cramer, A., Visser, I., Middeldorp, C., Lubke, G., Boomsma, D., & Borsboom, D. (2012). Phenotypic complexity as genetic dark matter: A network explanation of missing heritability. Proceedings of the 42nd Annual Meeting of the Behavior-Genetics-Association .
  • Blaazer, T. & Visser, I. (2006). Estimating Correlations and Reliabilities of Implicit and Explicit Tests Using a Latent Variable Approach. Proceedings of the Annual Meeting of the Cognitive Science Society .
  • Jansen, B. R., Raijmakers, M. E., & Visser, I. (2006). Learning on the Balance Scale Task. Proceedings of the Annual Meeting of the Cognitive Science Society .
  • Visser, I., Blaazer, T., et al. (2006). Estimating correlations and reliabilities of implicit and explicit tests using a latent variable approach. Proceedings of the Annual Meeting of the Cognitive Science Society .
  • Huizinga, M., Visser, I., Hamaker, E., & van der Molen, M. (2005). The development of executive control from childhood through young-adulthood: A latent variables approach. Fourteenth Conference of the European Society for Cognitive Psychology: Proceedings .
  • Visser, I., Tagaro, J., & Huizinga, H. (2005). A Meta-analysis of the Effects of the Secondary Tasks and Stimulus Complexity on Implicit Learning. Fourteenth Conference of the European Society for Cognitive Psychology: Proceedings .
  • Visser, I., Raijmakers, M. E., & Molenaar, P. C. (2001). Hidden Markov Model Model Interpretations of Neural Networks. Connectionist Models of Learning, Development and Evolution: Proceedings of the Sixth Neural Computation and Psychology Workshop, Li{`e}ge, Belgium, 16-18 September 2000 .
  • Visser, I., Raijmakers, M., & Molenaar, P. (2000). Reaction times and predictions in sequence learning: A comparison. Twenty-second annual conference of the Cognitive Science Society .
  • Visser, I., Raijmakers, M., Molenaar, P., et al. (1998). Statistical properties of hidden Markov models. International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling .

Books

  • Visser, I. & Speekenbrink, M. (2022). Mixture and Hidden Markov Models with R .
  • Visser, I. (2002). Rules and associations: hidden Markov models and neural networks in the psychology of learning .