@article{BuerkiAlarioVasishth2022,
  author    = {B{\"u}rki, Audrey and Alario, F-Xavier and Vasishth, Shravan},
  title     = {When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm},
  series = {Quarterly Journal of Experimental Psychology},
  volume    = {76},
  journal   = {Quarterly Journal of Experimental Psychology},
  number    = {6},
  publisher = {Sage Publications},
  address   = {London},
  issn      = {1747-0218},
  doi       = {10.1177/17470218221114644},
  pages     = {1410 -- 1430},
  year      = {2022},
  abstract  = {In the picture-word interference paradigm, participants name pictures while ignoring a written or spoken distractor word. Naming times to the pictures are slowed down by the presence of the distractor word. The present study investigates in detail the impact of distractor and target word properties on picture naming times, building on the seminal study by Miozzo and Caramazza. We report the results of several Bayesian meta-analyses based on 26 datasets. These analyses provide estimates of effect sizes and their precision for several variables and their interactions. They show the reliability of the distractor frequency effect on picture naming latencies (latencies decrease as the frequency of the distractor increases) and demonstrate for the first time the impact of distractor length, with longer naming latencies for trials with longer distractors. Moreover, distractor frequency interacts with target word frequency to predict picture naming latencies. The methodological and theoretical implications of these findings are discussed.},
  language  = {en}
}
@article{NicenboimVasishthRoesler2020,
  author    = {Nicenboim, Bruno and Vasishth, Shravan and R{\"o}sler, Frank},
  title     = {Are words pre-activated probabilistically during sentence comprehension?},
  series = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience},
  volume    = {142},
  journal   = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience},
  publisher = {Elsevier Science},
  address   = {Oxford},
  issn      = {0028-3932},
  doi       = {10.1016/j.neuropsychologia.2020.107427},
  pages     = {27},
  year      = {2020},
  abstract  = {Several studies (e.g., Wicha et al., 2003b; DeLong et al., 2005) have shown that readers use information from the sentential context to predict nouns (or some of their features), and that predictability effects can be inferred from the EEG signal in determiners or adjectives appearing before the predicted noun. While these findings provide evidence for the pre-activation proposal, recent replication attempts together with inconsistencies in the results from the literature cast doubt on the robustness of this phenomenon. Our study presents the first attempt to use the effect of gender on predictability in German to study the pre-activation hypothesis, capitalizing on the fact that all German nouns have a gender and that their preceding determiners can show an unambiguous gender marking when the noun phrase has accusative case. Despite having a relatively large sample size (of 120 subjects), both our preregistered and exploratory analyses failed to yield conclusive evidence for or against an effect of pre-activation. The sign of the effect is, however, in the expected direction: the more unexpected the gender of the determiner, the larger the negativity. The recent, inconclusive replication attempts by Nieuwland et al. (2018) and others also show effects with signs in the expected direction. We conducted a Bayesian random-ef-fects meta-analysis using our data and the publicly available data from these recent replication attempts. Our meta-analysis shows a relatively clear but very small effect that is consistent with the pre-activation account and demonstrates a very important advantage of the Bayesian data analysis methodology: we can incrementally accumulate evidence to obtain increasingly precise estimates of the effect of interest.},
  language  = {en}
}