R scripts and sample data for running a multiverse analysis of individual differences data on statistical learning and language
Sample data and code for models provided by Jessica Hall
Please cite Hall et al., 2019 Frontiers when referencing these data or models. Abbreviations are described in Table 6 of this article.
Note about data:
This is a SUBSET of the full dataset used in the article. For full datasets, please submit a request via github or the corresponding email address listed in the above article.
Data has been prescreened to remove trials with aberrant movements, that exceeded the time requirments, or were not experimental trials.
For VB1 models, consistency is the dependent variable. It is the measure of whether the participant's choice matched the bias of the verb on that trial. It is coded as 1 if they match and 0 if they do not match.
For VB2, VB3, and VB4 models, MD is the dependent variable. This stands for the maximum deviation of the mouse trajectory from a straight line from the trajectory's start to end points for that trial. MDs that are negative mean the trajectory curved in a direction away from the competitor picture, whereas MDs that are positive curved toward the competitor picture. MDs near 0 indicate a relatively straight trajectory.