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There is no belief update bias for neutral events: failure to replicate Burton et al. (2022)

In a recent paper, Burton et al. claim that individuals update beliefs to a greater extent when learning an event is less likely compared to more likely than expected. Here, we investigate Burton’s et al.’s, findings. First, we show how Burton et al.’s data do not in fact support a belief update bia...

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Detalles Bibliográficos
Autores principales: Garrett, Neil, Sharot, Tali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Routledge 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591604/
https://www.ncbi.nlm.nih.gov/pubmed/38013976
http://dx.doi.org/10.1080/20445911.2023.2245112
Descripción
Sumario:In a recent paper, Burton et al. claim that individuals update beliefs to a greater extent when learning an event is less likely compared to more likely than expected. Here, we investigate Burton’s et al.’s, findings. First, we show how Burton et al.’s data do not in fact support a belief update bias for neutral events. Next, in an attempt to replicate their findings, we collect a new data set employing the original belief update task design, but with neutral events. A belief update bias for neutral events is not observed. Finally, we highlight the statistical errors and confounds in Burton et al.’s design and analysis. This includes mis-specifying a reinforcement learning approach to model the data and failing to follow standard computational model fitting sanity checks such as parameter recovery, model comparison and out of sample prediction. Together, the results find little evidence for biased updating for neutral events.