TY  - JOUR
A1  - Rabe, Maximilian Michael
A1  - Chandra, Johan
A1  - Krügel, André
A1  - Seelig, Stefan A.
A1  - Vasishth, Shravan
A1  - Engbert, Ralf
T1  - A bayesian approach to dynamical modeling of eye-movement control in reading of normal, mirrored, and scrambled texts
JF  - Psychological Review
N2  - In eye-movement control during reading, advanced process-oriented models have been developed to reproduce behavioral data. So far, model complexity and large numbers of model parameters prevented rigorous statistical inference and modeling of interindividual differences. Here we propose a Bayesian approach to both problems for one representative computational model of sentence reading (SWIFT; Engbert et al., Psychological Review, 112, 2005, pp. 777-813). We used experimental data from 36 subjects who read the text in a normal and one of four manipulated text layouts (e.g., mirrored and scrambled letters). The SWIFT model was fitted to subjects and experimental conditions individually to investigate between- subject variability. Based on posterior distributions of model parameters, fixation probabilities and durations are reliably recovered from simulated data and reproduced for withheld empirical data, at both the experimental condition and subject levels. A subsequent statistical analysis of model parameters across reading conditions generates model-driven explanations for observable effects between conditions.
KW  - reading eye movements
KW  - dynamical models
KW  - Bayesian inference
KW  - oculomotor
KW  - control
KW  - individual differences
Y1  - 2021
U6  - https://doi.org/10.1037/rev0000268
SN  - 0033-295X
SN  - 1939-1471
VL  - 128
IS  - 5
SP  - 803
EP  - 823
PB  - American Psychological Association
CY  - Washington
ER  -