@article{VasishthMertzenJaegeretal.2018, author = {Vasishth, Shravan and Mertzen, Daniela and Jaeger, Lena A. and Gelman, Andrew}, title = {The statistical significance filter leads to overoptimistic expectations of replicability}, series = {Journal of memory and language}, volume = {103}, journal = {Journal of memory and language}, publisher = {Elsevier}, address = {San Diego}, issn = {0749-596X}, doi = {10.1016/j.jml.2018.07.004}, pages = {151 -- 175}, year = {2018}, abstract = {It is well-known in statistics (e.g., Gelman \& Carlin, 2014) that treating a result as publishable just because the p-value is less than 0.05 leads to overoptimistic expectations of replicability. These effects get published, leading to an overconfident belief in replicability. We demonstrate the adverse consequences of this statistical significance filter by conducting seven direct replication attempts (268 participants in total) of a recent paper (Levy \& Keller, 2013). We show that the published claims are so noisy that even non-significant results are fully compatible with them. We also demonstrate the contrast between such small-sample studies and a larger-sample study; the latter generally yields a less noisy estimate but also a smaller effect magnitude, which looks less compelling but is more realistic. We reiterate several suggestions from the methodology literature for improving current practices.}, language = {en} } @article{MertzenLagoVasishth2021, author = {Mertzen, Daniela and Lago, Sol and Vasishth, Shravan}, title = {The benefits of preregistration for hypothesis-driven bilingualism research}, series = {Bilingualism : language and cognition}, volume = {24}, journal = {Bilingualism : language and cognition}, number = {5}, publisher = {Cambridge Univ. Press}, address = {Cambridge}, issn = {1366-7289}, doi = {10.1017/S1366728921000031}, pages = {807 -- 812}, year = {2021}, abstract = {Preregistration is an open science practice that requires the specification of research hypotheses and analysis plans before the data are inspected. Here, we discuss the benefits of preregistration for hypothesis-driven, confirmatory bilingualism research. Using examples from psycholinguistics and bilingualism, we illustrate how non-peer reviewed preregistrations can serve to implement a clean distinction between hypothesis testing and data exploration. This distinction helps researchers avoid casting post-hoc hypotheses and analyses as confirmatory ones. We argue that, in keeping with current best practices in the experimental sciences, preregistration, along with sharing data and code, should be an integral part of hypothesis-driven bilingualism research.}, language = {en} } @article{JaegerMertzenVanDykeetal.2020, author = {J{\"a}ger, Lena Ann and Mertzen, Daniela and Van Dyke, Julie A. and Vasishth, Shravan}, title = {Interference patterns in subject-verb agreement and reflexives revisited}, series = {Journal of memory and language}, volume = {111}, journal = {Journal of memory and language}, publisher = {Elsevier}, address = {San Diego}, issn = {0749-596X}, doi = {10.1016/j.jml.2019.104063}, pages = {21}, year = {2020}, abstract = {Cue-based retrieval theories in sentence processing predict two classes of interference effect: (i) Inhibitory interference is predicted when multiple items match a retrieval cue: cue-overloading leads to an overall slowdown in reading time; and (ii) Facilitatory interference arises when a retrieval target as well as a distractor only partially match the retrieval cues; this partial matching leads to an overall speedup in retrieval time. Inhibitory interference effects are widely observed, but facilitatory interference apparently has an exception: reflexives have been claimed to show no facilitatory interference effects. Because the claim is based on underpowered studies, we conducted a large-sample experiment that investigated both facilitatory and inhibitory interference. In contrast to previous studies, we find facilitatory interference effects in reflexives. We also present a quantitative evaluation of the cue-based retrieval model of Engelmann, Jager, and Vasishth (2019).}, language = {en} }