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  - 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  -