- A tutorial on fitting Bayesian linear mixed models using
abstract: With the arrival of the R packages nlme and lme4, linear mixed models (LMMs) have come to be widely used in psychology, cognitive science, and related areas. In this tutorial, we provide a practical introduction to fitting LMMs in a Bayesian framework using the probabilistic programming language Stan. Although the Bayesian framework has several important advantages, specifying a Bayesian model requires quite a lot of background knowledge compared to frequentist tools like lme4. This tutorial provides the necessary background through two detailed examples of self-paced reading studies with repeated measures. One is a two-condition design, and the other a 2×2 factorial design. These two examples can easily be extended to more complex factorial designs. The data and code associated with this tutorial are available as a supplement.
- Sentence comprehension in aphasia: Eye-tracking reveals delayed morphological cue integration and late parsing commitments
abstract: Comprehension of non-canonical sentences can be difficult for individuals with aphasia (IWA). It is still unclear to which extent morphological cues like case-marking or verb inflection may influence IWA’s performance or even help to override deficits in sentence comprehension. Until now, studies have mainly used offline methods to draw inferences about syntactic deficits and, so far, only a few studies have looked at online syntactic processing in aphasia. We investigated sentence processing in German IWA by combining an offline (sentence-picture matching) and online (eye-tracking in the visual-world paradigm) method. Our goal was to determine whether IWA are capable of using inflectional morphology (number-agreement markers on verbs and case markers in noun phrases) as a cue to sentence interpretation. We report results of two visual-world experiments using German reversible SVO and OVS sentences. In each study, there were eight IWA and 20 age-matched controls. Experiment 1 targeted the role of case-morphology, while Experiment 2 looked at processing of number-agreement cues at the verb in case-ambiguous sentences. IWA showed deficits in using both types of morphological markers as a cue to non-canonical sentence interpretation and the results indicate that in aphasia, processing of case-marking cues is more vulnerable as compared to verb-agreement morphology. However, the online data revealed that IWA are in principle capable of successfully computing morphological cues, but the integration of morphological information is delayed as compared to age-matched controls. Furthermore, we found striking differences between controls and IWA regarding subject-before-object parsing predictions. While in case-unambiguous sentences IWA showed evidence for early subject-before-object parsing commitments, they exhibited no straightforward subject-first bias in case-ambiguous sentences, although controls did so for ambiguous structures. IWA delayed their parsing decisions in case-ambiguous sentences until unambiguous morphological information, such as a subject-verb-number-agreement cue, was available. We attribute the differential results for processing of case and agreement markers to differences in the degree of reliability of both morphological cues. We ascribe our findings for erroneous processing of case-unambiguous sentences in aphasia to late parsing commitments and failures in integrating case cues on time. For processing of case-ambiguous sentences in aphasia, we suggest that IWA adopt a wait-and-see strategy and make parsing commitments only when the agreement cue at the verb prompts a particular sentence structure. Our results for IWA further point to deficits in predictive processes during sentence comprehension.
Tuesday, October 14, 2014
Two new papers: Hanne et al, and Sorensen and Vasishth
We just submitted two new papers: