Book in preparation
Nicenboim, B., D. Schad, and S. Vasishth An Introduction to Bayesian Data Analysis for Cognitive Science. [read]
Under review
[bibtex]
Boelders, S. M., B. Nicenboim, E. Butterbrod, W. de Baene, E. Postma, G. Rutten, L. Ong, and K. Gehring (2024). “Predicting cognitive function three months after surgery in patients with a glioma”. under review. DOI: 10.1101/2024.10.08.24315076. [read]
Boelders, S., B. Nicenboim, E. Postma, G. Rutten, K. Gehring, and L. Ong (2024). “Modeling uncertainty in individual predictions of cognitive functioning for untreated glioma patients using Bayesian regression”. under review. DOI: 10.1101/2024.10.08.24315003. [read]
Dubova, M., S. Chandramouli, G. Gigerenzer, P. Grünwald, W. Holmes, T. Lombrozo, M. Marelli, S. Musslick, B. Nicenboim, L. Ross, et al. (2024). “Is Occam’s razor losing its edge? New perspectives on the principle of model parsimony”. under review. DOI: 10.31222/osf.io/bs5xe. [read]
Published (or accepted) in peer-reviewed journals
[bibtex]
2024
Schad, D. J., B. Nicenboim, and S. Vasishth (2024). “Data aggregation can lead to biased inferences in Bayesian linear mixed models and Bayesian analysis of variance.” In: Psychological Methods. ISSN: 1082-989X. DOI: 10.1037/met0000621.
2023
Doorn, J. van, J. M. Haaf, A. M. Stefan, E. Wagenmakers, G. E. Cox, C. P. Davis-Stober, A. Heathcote, D. W. Heck, M. Kalish, D. Kellen, et al. (2023). “Bayes Factors for Mixed Models: a Discussion”. In: Computational Brain & Behavior 6.1, pp. 140-158. ISSN: 2522-087X. DOI: 10.1007/s42113-022-00160-3. [read]
Vasishth, S., H. Yadav, D. J. Schad, and B. Nicenboim (2023). “Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics”. In: Computational Brain & Behavior 6.1, pp. 102-126. ISSN: 2522-087X. DOI: 10.1007/s42113-021-00125-y. [read]
Ben-Artzi, I., Y. Kessler, B. Nicenboim, and N. Shahar (2023). “Computational mechanisms underlying latent inverse value updating of unchosen actions”. In: Science Advances 9.42, p. eadi2704. DOI: 10.1126/sciadv.adi2704. [read]
2022
Stone, K., B. Nicenboim, S. Vasishth, and F. Rösler (2022). “Understanding the effects of constraint and predictability in ERP”. In: Neurobiology of Language, pp. 1-71. ISSN: 2641-4368. DOI: 10.1162/nol_a_00094. [read] [code/data]
Patterson, C., P. B. Schumacher, B. Nicenboim, J. Hagen, and A. Kehler (2022). “A Bayesian approach to German personal and demonstrative pronouns”. In: Frontiers in Psychology, Language Sciences 12. ISSN: 1664-1078. DOI: 10.3389/fpsyg.2021.672927. eprint: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.672927/abstract. [read]
Schad, D. J., B. Nicenboim, P. Bürkner, M. Betancourt, and S. Vasishth (2022). “Workflow Techniques for the Robust Use of Bayes Factors”. In: Psychological methods. ISSN: 1082-989X. DOI: 10.1037/met0000472. [read] [code/data]
Albert, A. and B. Nicenboim (2022). “Modeling Sonority in Terms of Pitch Intelligibility With the Nucleus Attraction Principle”. In: Cognitive Science 46.7, p. e13161. DOI: doi.or1/cogs.13161. [read] [code/data]
2021
Lisson, P., D. Pregla, B. Nicenboim, D. Paape, M. L. van het Nederend, F. Burchert, N. Stadie, D. Caplan, and S. Vasishth (2021). “A computational evaluation of two models of retrieval processes in sentence processing in aphasia”. In: Cognitive Science 45.4. DOI: 10.1111/cogs.12956. [read]
2020
Nicenboim, B., S. Vasishth, and F. Rösler (2020). “Are words pre-activated probabilistically during sentence comprehension? Evidence from new data and a Bayesian random-effects meta-analysis using publicly available data”. In: Neuropsychologia 142, p. 107427. ISSN: 0028-3932. DOI: 10.1016/j.neuropsychologia.2020.107427. [read]
2019
Vasishth, S., B. Nicenboim, F. Engelmann, and F. Burchert (2019). “Computational models of retrieval processes in sentence processing”. In: Trends in Cognitive Sciences 23.11, pp. 968 - 982. ISSN: 1364-6613. DOI: 10.1016/j.tics.2019.09.003. [read]
2018
Nicenboim, B., S. Vasishth, F. Engelmann, and K. Suckow (2018). “Exploratory and confirmatory analyses in sentence processing: A case study of number interference in German”. In: Cognitive Science 42.S4, pp. 1075–1100. DOI: 10.1111/cogs.12589. [read] [code/data]
Nicenboim, B., T. B. Roettger, and S. Vasishth (2018). “Using meta-analysis for evidence synthesis: The case of incomplete neutralization in German”. In: Journal of Phonetics 70, pp. 39–55. DOI: 10.1016/j.wocn.2018.06.001. [read] [code/data]
Vasishth, S., B. Nicenboim, M. E. Beckman, F. Li, and E. Kong (2018). “Bayesian data analysis in the phonetic sciences: A tutorial introduction”. In: Journal of Phonetics 71, pp. 147–161. DOI: 10.1016/j.wocn.2018.07.008. [read] [code/data]
Nicenboim, B. and S. Vasishth (2018). “Models of Retrieval in Sentence Comprehension: A computational evaluation using Bayesian hierarchical modeling”. In: Journal of Memory and Language 99, pp. 1 –34. ISSN: 0749-596X. DOI: 10.1016/j.jml.2017.08.004. [read] [code/data]
2017
Paape, D., B. Nicenboim, and S. Vasishth (2017). “Does antecedent complexity affect ellipsis processing? An empirical investigation”. In: Glossa: A journal of general linguistics. 2.1, p. 71. DOI: 10.5334/gjgl.290. [read]
2016
Nicenboim, B., P. Logačev, C. Gattei, and S. Vasishth (2016). “When high-capacity readers slow down and low-capacity readers speed up: Working memory and locality effects”. In: Frontiers in Psychology 7.280. ISSN: 1664-1078. DOI: 10.3389/fpsyg.2016.00280 . eprint: https://www.frontiersin.org/articles/10.3389/fpsyg.2016.00280/full. [read] [code/data]
Nicenboim, B. and S. Vasishth (2016). “Statistical methods for linguistic research: Foundational Ideas - Part II”. In: Language and Linguistics Compass 10.11, pp. 591–613. ISSN: 1749-818X. DOI: 10.1111/lnc3.12207. [read]
Vasishth, S. and B. Nicenboim (2016). “Statistical Methods for Linguistic Research: Foundational Ideas - Part I”. In: Language and Linguistics Compass 10.8, pp. 349–369. ISSN: 1749-818X. DOI: 10.1111/lnc3.12201. [read]
2015
Nicenboim, B., S. Vasishth, C. Gattei, M. Sigman, and R. Kliegl (2015). “Working memory differences in long-distance dependency resolution”. In: Frontiers in Psychology 6.312. ISSN: 1664-1078. DOI: 10.3389/fpsyg.2015.00312. [read] [code/data]
Short peer-reviewed papers in conferences [bibtex]
Nicenboim, B. (2023). “The CoFI Reader: A Continuous Flow of Information approach to modeling reading”. In: MathPsych/ICCM/EMPG. University of Amsterdam, the Netherlands. [read]
Nicenboim, B. (2018). “The implementation of a model of choice: The (truncated) linear ballistic accumulator”. In: StanCon. Aalto University, Helsinki, Finland. DOI: 10.5281/zenodo.1465990. [read] [talk]
Vasishth, S., N. Chopin, R. Ryder, and B. Nicenboim (2017). “Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses”. In: Proceedings of Cognitive Science Conference. London, UK. [read]
Vasishth, S., L. Jaeger, and B. Nicenboim (2017). “Feature overwriting as a finite mixture process: Evidence from comprehension data”. In: Proceedings of MathPsych/ICCM Conference. Warwick, UK. [read]
Nicenboim, B. and S. Vasishth (2017). “Models of Retrieval in Sentence Comprehension”. In: StanCon. (superseeded by 10.1016/j.jml.2017.08.004). Columbia University New York, NY. [talk]
Unpublished manuscripts
[bibtex]
Vasishth, S., B. Nicenboim, N. Chopin, and R. Ryder (2017). “Bayesian hierarchical finite mixture models of reading times: A case study”. unpublished. DOI: 10.17605/OSF.IO/FWX3S. [read]
Conferences
2022
Stone, K., B. Nicenboim, S. Vasishth, and F. Rösler (2022). “Dissociating constraint and predictability in ERP: Evidence from German”. In: Proceedings of the 35th annual conference on Human Sentence Processing (HSP). Santa Cruz, USA. [Poster]
2021
Stone, K., S. Vasishth, F. Rösler, and B. Nicenboim (2021). “Maximising ERP Resources Using a Sequential Bayes Factor Approach to Sample Size”. In: Architectures and Mechanisms for Language Processing (AMLaP). Université de Paris, France. [Short talk]
Patterson, C., P. B. Schumacher, B. Nicenboim, J. Hagen, and A. Kehler (2021). “German pronoun use follows Bayesian principles”. In: Proceedings of Annual CUNY Sentence Processing Conference, University of Pennsylvania. [Short talk]
2020
Lisson, P., D. Pregla, D. Paape, B. Nicenboim, N. Stadie, F. Burchert, and S. Vasishth (2020). “Computational models of retrieval processes in sentence comprehension in aphasia”. In: Architectures and Mechanisms for Language Processing (AMLaP). University of Potsdam, Germany. [talk]
Albert, A. and B. Nicenboim (2020). “Incorporating continuity in phonological models of the syllable using NAP”. In: LabPhon17. [Poster]
2019
Nicenboim, B. (2019). “Bayesian inference: Obstacles and opportunities”. In: 8th Biennial International Conference on the Linguistics of Contemporary English (BICLCE), Bamberg, Germany. [talk]
Lisson, P., B. Nicenboim, S. Vasishth, and D. Paape (2019). “Models of retrieval in sentence comprehension in aphasia”. In: StanCon. Cambridge, UK. [Poster]
Lisson, P., M. van het Nederend, D. Pregla, S. Vasishth, B. Nicenboim, and D. Paape (2019). “Competing models of retrieval in sentence processing: The case of aphasia”. In: Architectures and Mechanisms for Language Processing (AMLaP). Institute of Cognitive Neuroscience and Centre for Language and Brain, Higher School of Economics, Russia. [Poster]
2018
Guerra, E., B. Nicenboim, and A. V. Helo (2018). “A crack in the crystall ball: Evidence against pre-activation of gender features in sentence comprehension”. In: Architectures and Mechanisms for Language Processing (AMLaP). Titanic Hotel Chaussee Berlin, Germany. [Poster]
Nicenboim, B. and S. Vasishth (2018). “Bayesian cognitive models of memory retrieval processes: A case study ”. In: 51. Kongress der Deutschen Gesellschaft für Psychologie. Bayesian statistics as a coherent approach to psychologists’ statistical and methodological problems. Goethe-Universität Frankfurt, Germany. [Talk]
2017
Albert, A. and B. Nicenboim (2017). “Linking sonority with periodic energy: Preliminary findings from production and perception”. In: 3rd International Workshop on Dynamic Modeling, Cologne, Germany. [Talk]
Nicenboim, B. and S. Vasishth (2017). “Models of retrieval in sentence comprehension: A computational evaluation using Bayesian hierarchical modeling”. In: Proceedings of the Annual CUNY Sentence Processing Conference. Massachusetts Institute of Technology, Boston, MA, USA. [Poster]
2016
Nicenboim, B., F. Engelmann, K. Suckow, and S. Vasishth (2016). “Number interference as predicted by cue-based retrieval”. In: Architectures and Mechanisms for Language Processing (AMLaP). Bilbao, Spain. [Poster]
2015
Nicenboim, B., F. Engelmann, K. Suckow, and S. Vasishth (2015). “Fail fast or succeed slowly: Good-enough processing can mask interference effects”. In: International Conference on Cognitive Modeling (ICCM). [Poster]
Nicenboim, B., P. Logacev, C. Gattei, and S. Vasishth (2015). “When high-capacity readers slow down and low-capacity readers speed up: Working memory differences in unbounded dependencies”. In: Proceedings of Annual CUNY Sentence Processing Conference. University of Southern California, Los Angeles, CA. [Poster]
Nicenboim, B., K. Suckow, and S. Vasishth (2015). “Good-enough processing can mask interference effects”. In: Proceedings of Annual CUNY Sentence Processing Conference. University of Southern California, Los Angeles, CA. [Poster]
2014
Nicenboim, B., P. Logacev, C. Gattei, and S. Vasishth (2014). “When high-capacity readers slow down and low-capacity readers speed up: Working memory differences in unbounded dependencies for German and Spanish readers”. In: Mental Architecture for Processing and Learning of Language (MAPLL). Tokyo, Japan. [Talk]
Nicenboim, B., S. Vasishth, and R. Kliegl (2014). “Readers with less cognitive control are more affected by surprising content: Evidence from a self-paced reading experiment in German”. In: Mental Architecture for Processing and Learning of Language (MAPLL). Tokyo, Japan. [Talk]
Nicenboim, B., S. Vasishth, and R. Kliegl (2014). “Readers with less cognitive control are more affected by surprising content”. In: Architectures and Mechanisms for Language Processing (AMLaP). Edinburgh, UK. [Poster]
Nicenboim, B., S. Vasishth, R. Kliegl, C. Gattei, and M. Sigman (2014). “Working-memory capacity modulates antilocality effects in syntactic dependencies”. In: Proceedings of Annual CUNY Sentence Processing Conference. The Ohio State University, Columbus, OH. [Poster]
2013
Nicenboim, B., S. Vasishth, C. Gattei, P. Logačev, and M. Sigman (2013). “The effect of distance on unbounded dependencies: An individual differences perspective”. In: Architectures and Mechanisms for Language Processing (AMLaP). Aix-Marseille Université, Marseille, France. [Poster]
2012
Nicenboim, B. (2012). “Processing of filler-gap dependencies in Complex NP islands: Evidence from Hebrew”. In: Proceedings of Annual CUNY Sentence Processing Conference, New York, NY. [Poster]
Nicenboim, B. (2012). “Processing Complex NP islands in Hebrew”. In: Proceedings of Generative Linguistics in the Old World Conference (GLOW), Potsdam, Germany. [Talk]