This page contains a list of (co-)authored publications and conference presentations. Please contact me if any of those are not accessible for you. To look at my CV, click here.
Preprints
- Rabe, M. M.
, Paape, D. , Vasishth, S. , & Engbert, R. (2021). Dynamical cognitive modeling of syntactic processing and eye movement control in reading. Manuscript in preparation. PsyArxiv
Journal Articles
- Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , Vasishth, S. , & Engbert, R. (in press). A Bayesian approach to dynamical modeling of eye-movement control in reading of normal, mirrored, and scrambled texts. Psychological Review. DOI PsyArxiv
- Engbert, R. , Rabe, M. M. , Kliegl, R. , & Reich, S. (2021). Sequential data assimilation of the SEIR model for COVID-19. Bulletin of Mathematical Biology, 83(1). DOI medRxiv PDF
- Rabe, M. M. , Vasishth, S. , Hohenstein, S. , Kliegl, R. , & Schad, D. J. (2020). hypr: An R package for hypothesis-driven contrast coding. The Journal of Open Source Software, 5(48), 2134. DOI PDF
- Seelig, S. A. , Rabe, M. M. , Malem-Shinitski, N. , Risse, S. , Reich, S. , & Engbert, R. (2020). Bayesian parameter estimation for the SWIFT model of eye-movement control during reading. Journal of Mathematical Psychology, 95. DOI arXiv PDF
- Masson, M. E. J. , Rabe, M. M. , & Kliegl, R. (2017). Modulation of additive and interactive effects by trial history revisited. Memory & Cognition, 45(3), 480–492. DOI PDF
Software
- Rabe, M. M. , Schad, D. J. , Vasishth, S. , & Kliegl, R. (2019). hypr: Hypothesis matrix translation [R package]. URL
- Rabe, M. M. , Kliegl, R. , & Schad, D. J. (2019). designr: Balanced factorial designs with crossed random and fixed factors [R package]. URL
Theses
- Rabe, M. M. (2018). Generalized linear mixed modeling of Signal Detection Theory (Master of Science). Supervisors: D. S. Lindsay , M. E. J. Masson , and A. Krawitz. University of Victoria, BC, Canada. HDL PDF
- Rabe, M. M. (2015). Mixed model analysis of trial history in naming experiments (Bachelor of Science). Supervisors: R. Kliegl and M. E. J. Masson . Universität Potsdam, Germany. URN PDF
Presentations
- Rabe, M. M. (November 2019). Eye-movement control during reading: Bayesian parameter inference of the dynamical SWIFT model. Invited talk presented at University of Victoria, BC, Canada.
- Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , & Engbert, R. (November 2019). Bayesian inference of dynamical cognitive and oculomotor processes in the SWIFT model of reading. Poster presented at Psychonomic Society 60th Annual Meeting, Montréal, QC, Canada. DOI PDF
- Seelig, S. A. , Rabe, M. M. , Malem-Shinitski, N. , Reich, S. , & Engbert, R. (September 2019). Bayesian parameter estimation for the SWIFT model of eye-movement control during reading. Poster presented at Cognitive Computational Neuroscience (CCN) 2019, Berlin, Germany. DOI
- Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , & Engbert, R. (August 2019). Bayesian inference of the SWIFT model: Reading mirrored, scrambled, and normal texts. Poster presented at European Conference on Eye Movements (ECEM) 2019, Alicante, Spain. DOI PDF
- Rabe, M. M. , Seelig, S. A. , Chandra, J. , Vasishth, S. , Reich, S. , & Engbert, R. (March 2019). Parameter inference and model comparison in dynamical cognitive models: SWIFT. Poster presented at 2nd SFB 1294 Data Assimilation Spring School, Dierhagen, Germany. PDF
- Rabe, M. M. , Kliegl, R. , & Lindsay, D. S. (November 2017). A Generalized linear mixed model approach to signal detection theory in recognition memory experiments. Poster presented at Psychonomic Society 58th Annual Meeting, Vancouver, BC, Canada.
- Rabe, M. M. , Kliegl, R. , & Lindsay, D. S. (May 2017). Generalized linear mixed model of signal detection theory. Poster presented at NOWCAM, Burnaby, BC, Canada.
- Fallow, K. M. , Rabe, M. M. , & Lindsay, D. S. (November 2015). Recognition memory response bias for paintings, words, and faces. Poster presented at Psychonomic Society 56th Annual Meeting, Chicago, IL, USA.