Linguistic Evidence (LE 2024) read more
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Application for Short-Term Fellowships available in 2024 read more
openHPI-Course about “Introduction to Bayesian Data Analysis” read more


Scientific service and infrastructure project

PI(s): Prof. Dr. Shravan Vasishth & Prof. Dr. Ralf Engbert

This project provides support to the CRC by advising other projects on experiment design and statistical data analysis, helping projects to preregister their primary statistical analyses using the Open Science Foundation, and helping with the data management and archiving. This is achieved through four work packages that (1) provide support to the CRC in optimizing experiment design and analysis, (2) provide statistical education within the CRC, (3) assist in developing and maintaining a data repository to ensure preregistration, open access of data and code, and reproducibility, and (4) develop new statistical methods, computational tools, and software packages needed for the CRC, which will be made available in the public domain.



Prof. Dr. Ralf Engbert

Universität PotsdamCampus GolmDepartment PsychologieKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 4.0314476 Potsdam
(+49) 331 977-2140 E-Mail Link

Dr. Anna Laurinavichyute

Universität PotsdamCampus GolmDepartment LinguistikKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 3.3614476 Potsdam

Prof. Dr. Shravan Vasishth

Universität PotsdamCampus GolmDepartment LinguistikKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 2.3414476 Potsdam
(+49) 331 977-2457 E-Mail Link

David Ziegert

Universität PotsdamCampus GolmDepartment LinguistikKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 3.3414476 Potsdam
(+49) 331 977-231118 E-Mail


Types of publications:

- Peer-Reviewed: Papers, Journals, Books, Articles of the CRC
- Talk or Presentation: Talks, Presentations, Posters of the CRC
- SFB-Related: not produced in connection with the CRC, but are thematically appropriate
- Other: Papers, Journals, Books, Articles of the CRC, but not peer-reviewed

Quick-Search by "Type" :
Author(s)TitleYearPublished inLinksType
Rabe, M. M., Vasishth, S., Hohenstein, S., Kliegl, R., & Schad, D. J.hypr: An R package for hypothesis-driven contrast coding.2020The Journal of Open Source Software, 5(48), 2134. DOI: 10.21105/joss.02134Paper CodePeer-Reviewed
Engelmann, F., Jäger, L. A., & Vasishth, S.The effect of prominence and cue association in retrieval processes: A computational account.2019Cognitive Science, 43: e12800. DOI: 10.1111/cogs.12800Paper Data+Code Peer-Reviewed
Vasishth, S., Mertzen, D., Jäger, L.A., & Gelman, A.The statistical significance filter leads to overoptimistic expectations of replicability.2018Journal of Memory and Language, 103, 151-175. DOI: 10.1016/j.jml.2018.07.004Paper Data+Code Peer-Reviewed
Jäger, L. A., Mertzen, D., Van Dyke, J. A., & Vasishth, S.Interference patterns in subject-verb agreement and reflexives revisited: A large-sample study.2020Journal of Memory and Language, 111, 104063. DOI: 10.1016/j.jml.2019.104063Paper Data+Code Peer-Reviewed
Vasishth, S.Using Approximate Bayesian Computation for estimating parameters in the cue-based retrieval model of sentence processing.2020MethodsX, 7: 100850. DOI: 10.1016/j.mex.2020.100850Paper Data+Code Peer-Reviewed
Bürki, A., Elbuy, S., Madec, S., & Vasishth, S.What did we learn from forty years of research on semantic interference? A Bayesian meta-analysis.2020Journal of Memory and Language, 114: 104125. DOI: 10.1016/j.jml.2020.104125Paper Data+Code Peer-Reviewed
Schad, D. J., Vasishth, S., Hohenstein, S., & Kliegl, R.How to capitalize on a priori contrasts in linear (mixed) models: A tutorial.2020Journal of Memory and Language, 110: 104038. DOI: 10.1016/j.jml.2019.104038Paper CodePeer-Reviewed
Schad, D.J., Betancourt, M., & Vasishth, S.Toward a principled Bayesian workflow: A tutorial for cognitive science.2021Psychological Methods, 26(1), 103-126. DOI: 10.1037/met0000275Paper Data+Code Peer-Reviewed
Nicenboim, B.,  Roettger, T.B., & Vasishth, S.Using meta-analysis for evidence synthesis: The case of incomplete neutralization in German.2018Journal of Phonetics, 70 (Special Issue: Emerging Data Analysis in Phonetic Sciences), 39-55. DOI: 10.1016/j.wocn.2018.06.001Paper Data+Code Peer-Reviewed
Schad, D.J., Betancourt, M., & Vasishth, S.Toward a principled Bayesian workflow: A tutorial for cognitive science.2019Data+Code Other
Schad, D. J., & Vasishth, S. The posterior probability of a null hypothesis given a statistically significant research result.2019arXiv preprint.Paper Other
Schad, D. J., Hohenstein, S., Vasishth, S., & Kliegl, R.How to capitalize on a priori contrasts in linear (mixed) models: A tutorial.2018arXiv preprint.Paper Other
Nicenboim, B., & Vasishth, S. Models of retrieval in sentence comprehension: A computational evaluation using Bayesian hierarchical modeling.2018Journal of Memory and Language, 99(April 2018), 1-34. DOI: 10.1016/j.jml.2017.08.004SFB-Related
Nicenboim, B., Vasishth, S., Engelmann, F., & Suckow, K.Exploratory and confirmatory analyses in sentence processing: A case study of number interference in German.2018Cognitive Science, 42(Suppl. 4), 1075-1100. DOI: 10.1111/cogs.12589SFB-Related
Vasishth, S., Nicenboim, B., Beckman, M.E., Fangfang, L., & Kong, J.E.Bayesian data analysis in the phonetic sciences: A tutorial introduction.2018Journal of Phonetics, 71 (Special Issue: Emerging Data Analysis in Phonetic Sciences), 147-161. DOI: 10.1016/j.wocn.2018.07.008SFB-Related
Bürki, A., Elbuy, S., Madec, S., & Vasishth, S.What did we learn from forty years of research on semantic interference? A Bayesian meta-analysis.2020Poster presented at the 26th Architectures and Mechanisms of Language Processing (AMLaP 2020), University of Potsdam, Potsdam, Germany. 03 - 05 September.Talk or Presentation
Schad, D., Betancourt, M., & Vasishth, S.Toward a principled Bayesian workflow in cognitive science.2019Paper presented at the 14. Tagung der Fachgruppe Methoden & Evaluation der Deutschen Gesellschaft für Psychologie (FGME 2019), Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik (IPN), Kiel, Germany. 15 - 18 September.Talk or Presentation
Vasishth, S.The role of replication in Bayesian data analysis.2019Invited talk at the Lecture Series Psychological Science, Winter-Term 2019/2020, University of Hamburg, Hamburg, Germany. 18 December.Paper Talk or Presentation
Vasishth, S.Prenominal relatives clauses in Mandarin: Implications for theories of sentence processing.2019Invited talk at the GK Colloquium, Institut für Linguistik, Goethe-Universität Frankfurt, Frankfurt, Germany. 14 MayTalk or Presentation
Vasishth, S.Is pre-registration a bad idea or a very bad idea?2019Invited talk at the Humboldt-Universität zu Berlin, Berlin, Germany. 24 January.Talk or Presentation
Vasishth, S.Bayesian vs. frequentist data analysis: A comparison.2019Invited talk at the Block Seminar, SFB 1340 ''Matrix in Vision'', Berlin, Germany. 18 JanuarTalk or Presentation
Laurinavichyute, A., & von der Malsburg, T.Semantic Attraction in Sentence Comprehension.2022Cognitive Science, 46(2), e13086. DOI: 10.1111/cogs.13086Paper CodePeer-Reviewed
Schad, D. J., Nicenboim, B., Bürkner, P.-C., Betancourt, M., & Vasishth, S.Workflow techniques for the robust use of bayes factors.2022Psychological Methods. Advance Online Publication. DOI: 10.1037/met0000472Peer-Reviewed
Vasishth, S., Yadav, H., Schad, D. J., & Nicenboim, B.Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics.2022Computational Brain & Behavior. DOI: 10.1007/s42113-021-00125-yPaper Data+Code Peer-Reviewed
Vasishth, S., & Engelmann, F.Sentence Comprehension as a Cognitive Process: A Computational Approach.2021Cambridge: Cambridge University Press.SFB-Related
Laurinavichyute, A., Yadav, H., & Vasishth, S.Share the code, not just the data: A case study of the reproducibility of articles published in the Journal of Memory and Language under the open data policy.2022Journal of Memory and Language, 125, 104332. DOI: 10.1016/j.jml.2022.104332Paper Data+Code Peer-Reviewed
Ciaccio, L. A., & Veríssimo, J.Investigating variability in morphological processing with Bayesian distributional models.2022Psychonomic Bulletin & Review. DOI: 10.3758/s13423-022-02109-wPaper Data+Code Peer-Reviewed
Vasishth, ShravanSome Right Ways to Analyze (Psycho)Linguistic Data.2023Annual Review of Linguistics, 9(1), 273-291. DOI: 10.1146/annurev-linguistics-031220-010345Paper CodePeer-Reviewed
van Doorn, J., Haaf, J. M., Stefan, A. M., Wagenmakers, E.-J., Cox, G. E., Davis-Stober, C. P., et al.Bayes Factors for Mixed Models: a Discussion.2023Computational Brain & Behavior, 6(1), 140-158. DOI: 10.1007/s42113-022-00160-3Paper Peer-Reviewed
Vasishth, S.New directions in statistical analysis for experimental linguistics.2023London: Routledge DOI: