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. Number of citations from Google Scholar are current as of December 3, 2021.
Preprints
- Rabe, M. M.
, Lindsay, D. S. , & Kliegl, R. (2021). ROC asymmetry is not diagnostic of unequal residual variance in Gaussian signal detection theory. Manuscript in preparation. PsyArXiv - 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. 1 Citation PsyArXiv
Journal Articles
- Engbert, R. , Rabe, M. M. , Schwetlick, L. , Seelig, S. A. , Reich, S. , & Vasishth, S. (in press). Data assimilation in dynamical cognitive science. Topics in Cognitive Science.
- Rabe, M. M. , Chandra, J. , Krügel, A. , Seelig, S. A. , Vasishth, S. , & Engbert, R. (2021). A Bayesian approach to dynamical modeling of eye-movement control in reading of normal, mirrored, and scrambled texts. Psychological Review, 128(5), 803–823. 7 Citations 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, Article 1 (2021). 47 Citations 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), Article 2134. 7 Citations 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, Article 102313. 16 Citations 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. 7 Citations 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. 2 Citations HDL OCLC 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 DNB OCLC 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.