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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.
Members
Prof. Dr. Ralf Engbert
Universität PotsdamCampus GolmDepartment PsychologieKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 4.0314476 Potsdam
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
David Ziegert
Universität PotsdamCampus GolmDepartment LinguistikKarl-Liebknecht-Strasse 24-25, Haus 14, Raum 3.3414476 Potsdam
Publications
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- Other: Papers, Journals, Books, Articles of the CRC, but not peer-reviewed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) | Title | Year | Published in | Links | Type |
|---|---|---|---|---|---|
| Rabe, M. M., Vasishth, S., Hohenstein, S., Kliegl, R., & Schad, D. J. | hypr: An R package for hypothesis-driven contrast coding. | 2020 | The Journal of Open Source Software, 5(48), 2134. DOI: 10.21105/joss.02134 | Paper Code | Peer-Reviewed |
| Engelmann, F., Jäger, L. A., & Vasishth, S. | The effect of prominence and cue association in retrieval processes: A computational account. | 2019 | Cognitive Science, 43: e12800. DOI: 10.1111/cogs.12800 | Paper Data+Code | Peer-Reviewed |
| Vasishth, S., Mertzen, D., Jäger, L.A., & Gelman, A. | The statistical significance filter leads to overoptimistic expectations of replicability. | 2018 | Journal of Memory and Language, 103, 151-175. DOI: 10.1016/j.jml.2018.07.004 | Paper 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. | 2020 | Journal of Memory and Language, 111, 104063. DOI: 10.1016/j.jml.2019.104063 | Paper Data+Code | Peer-Reviewed |
| Vasishth, S. | Using Approximate Bayesian Computation for estimating parameters in the cue-based retrieval model of sentence processing. | 2020 | MethodsX, 7: 100850. DOI: 10.1016/j.mex.2020.100850 | Paper 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. | 2020 | Journal of Memory and Language, 114: 104125. DOI: 10.1016/j.jml.2020.104125 | Paper 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. | 2020 | Journal of Memory and Language, 110: 104038. DOI: 10.1016/j.jml.2019.104038 | Paper Code | Peer-Reviewed |
| Schad, D.J., Betancourt, M., & Vasishth, S. | Toward a principled Bayesian workflow: A tutorial for cognitive science. | 2021 | Psychological Methods, 26(1), 103-126. DOI: 10.1037/met0000275 | Paper Data+Code | Peer-Reviewed |
| Nicenboim, B., Roettger, T.B., & Vasishth, S. | Using meta-analysis for evidence synthesis: The case of incomplete neutralization in German. | 2018 | Journal of Phonetics, 70 (Special Issue: Emerging Data Analysis in Phonetic Sciences), 39-55. DOI: 10.1016/j.wocn.2018.06.001 | Paper Data+Code | Peer-Reviewed |
| Schad, D.J., Betancourt, M., & Vasishth, S. | Toward a principled Bayesian workflow: A tutorial for cognitive science. | 2019 | Data+Code | Other | |
| Schad, D. J., & Vasishth, S. | The posterior probability of a null hypothesis given a statistically significant research result. | 2019 | arXiv 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. | 2018 | arXiv preprint. | Paper | Other |
| Nicenboim, B., & Vasishth, S. | Models of retrieval in sentence comprehension: A computational evaluation using Bayesian hierarchical modeling. | 2018 | Journal of Memory and Language, 99(April 2018), 1-34. DOI: 10.1016/j.jml.2017.08.004 | SFB-Related | |
| Nicenboim, B., Vasishth, S., Engelmann, F., & Suckow, K. | Exploratory and confirmatory analyses in sentence processing: A case study of number interference in German. | 2018 | Cognitive Science, 42(Suppl. 4), 1075-1100. DOI: 10.1111/cogs.12589 | SFB-Related | |
| Vasishth, S., Nicenboim, B., Beckman, M.E., Fangfang, L., & Kong, J.E. | Bayesian data analysis in the phonetic sciences: A tutorial introduction. | 2018 | Journal of Phonetics, 71 (Special Issue: Emerging Data Analysis in Phonetic Sciences), 147-161. DOI: 10.1016/j.wocn.2018.07.008 | SFB-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. | 2020 | Poster 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. | 2019 | Paper 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. | 2019 | Invited 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. | 2019 | Invited talk at the GK Colloquium, Institut für Linguistik, Goethe-Universität Frankfurt, Frankfurt, Germany. 14 May | Talk or Presentation | |
| Vasishth, S. | Is pre-registration a bad idea or a very bad idea? | 2019 | Invited talk at the Humboldt-Universität zu Berlin, Berlin, Germany. 24 January. | Talk or Presentation | |
| Vasishth, S. | Bayesian vs. frequentist data analysis: A comparison. | 2019 | Invited talk at the Block Seminar, SFB 1340 ''Matrix in Vision'', Berlin, Germany. 18 Januar | Talk or Presentation | |
| Laurinavichyute, A., & von der Malsburg, T. | Semantic Attraction in Sentence Comprehension. | 2022 | Cognitive Science, 46(2), e13086. DOI: 10.1111/cogs.13086 | Paper Code | Peer-Reviewed |
| Schad, D. J., Nicenboim, B., Bürkner, P.-C., Betancourt, M., & Vasishth, S. | Workflow techniques for the robust use of bayes factors. | 2022 | Psychological Methods. Advance Online Publication. DOI: 10.1037/met0000472 | Peer-Reviewed | |
| Vasishth, S., Yadav, H., Schad, D. J., & Nicenboim, B. | Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics. | 2022 | Computational Brain & Behavior. DOI: 10.1007/s42113-021-00125-y | Paper Data+Code | Peer-Reviewed |
| Vasishth, S., & Engelmann, F. | Sentence Comprehension as a Cognitive Process: A Computational Approach. | 2021 | Cambridge: 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. | 2022 | Journal of Memory and Language, 125, 104332. DOI: 10.1016/j.jml.2022.104332 | Paper Data+Code | Peer-Reviewed |
| Ciaccio, L. A., & Veríssimo, J. | Investigating variability in morphological processing with Bayesian distributional models. | 2022 | Psychonomic Bulletin & Review. DOI: 10.3758/s13423-022-02109-w | Paper Data+Code | Peer-Reviewed |
| Vasishth, Shravan | Some Right Ways to Analyze (Psycho)Linguistic Data. | 2023 | Annual Review of Linguistics, 9(1), 273-291. DOI: 10.1146/annurev-linguistics-031220-010345 | Paper Code | Peer-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. | 2023 | Computational Brain & Behavior, 6(1), 140-158. DOI: 10.1007/s42113-022-00160-3 | Paper | Peer-Reviewed |