TY - JOUR A1 - Bürki, Audrey A1 - Alario, F-Xavier A1 - Vasishth, Shravan T1 - When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm JF - Quarterly Journal of Experimental Psychology N2 - 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. KW - Picture-word interference KW - Bayesian meta-analysis KW - distractor frequency Y1 - 2022 U6 - https://doi.org/10.1177/17470218221114644 SN - 1747-0218 SN - 1747-0226 VL - 76 IS - 6 SP - 1410 EP - 1430 PB - Sage Publications CY - London ER - TY - JOUR A1 - Jaeger, Lena A. A1 - Engelmann, Felix A1 - Vasishth, Shravan T1 - Similarity-based interference in sentence comprehension: Literature review and Bayesian meta-analysis JF - Journal of memory and language N2 - We report a comprehensive review of the published reading studies on retrieval interference in reflexive-/reciprocal-antecedent and subject-verb dependencies. We also provide a quantitative random-effects meta-analysis of eyetracking and self-paced reading studies. We show that the empirical evidence is only partly consistent with cue-based retrieval as implemented in the ACT-R-based model of sentence processing by Lewis and Vasishth (2005) (LV05) and that there are important differences between the reviewed dependency types. In non-agreement subject-verb dependencies, there is evidence for inhibitory interference in configurations where the correct dependent fully matches the retrieval cues. This is consistent with the LV05 cue-based retrieval account. By contrast, in subject-verb agreement as well as in reflexive-/reciprocal-antecedent dependencies, no evidence for inhibitory interference is found in configurations with a fully cue-matching subject/antecedent. In configurations with only a partially cue-matching subject or antecedent, the meta-analysis reveals facilitatory interference in subject-verb agreement and inhibitory interference in reflexives/reciprocals. The former is consistent with the LV05 account, but the latter is not. Moreover, the meta-analysis reveals that (i) interference type (proactive versus retroactive) leads to different effects in the reviewed dependency types and (ii) the prominence of the distractor strongly influences the interference effect. In sum, the meta-analysis suggests that the LV05 needs important modifications to account for the unexplained interference patterns and the differences between the dependency types. More generally, the meta-analysis provides a quantitative empirical basis for comparing the predictions of competing accounts of retrieval processes in sentence comprehension. (C) 2017 Elsevier Inc. All rights reserved. KW - Cue-based retrieval KW - Syntactic dependency processing KW - Interference KW - Bayesian meta-analysis KW - Agreement KW - Reflexives Y1 - 2017 U6 - https://doi.org/10.1016/j.jml.2017.01.004 SN - 0749-596X SN - 1096-0821 VL - 94 SP - 316 EP - 339 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - Nicenboim, Bruno A1 - Vasishth, Shravan A1 - Rösler, Frank T1 - Are words pre-activated probabilistically during sentence comprehension? BT - evidence from new data and a Bayesian random-effects meta-analysis using publicly available data JF - Neuropsychologia : an international journal in behavioural and cognitive neuroscience N2 - 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. KW - ERP KW - pre-activation KW - predictions KW - grammatical gender KW - Bayesian meta-analysis Y1 - 2020 U6 - https://doi.org/10.1016/j.neuropsychologia.2020.107427 SN - 0028-3932 SN - 1873-3514 VL - 142 PB - Elsevier Science CY - Oxford ER -