Benefits of multinomial processing tree models with discrete and continuous variables in memory research: an alternative modeling proposal to Juola et al. (2019).

Autor: Gutkin A; Department of Psychological Methods, Philipps-Universität Marburg, Marburg, Germany. anahi.gutkin@uam.es.; Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain. anahi.gutkin@uam.es., Suero M; Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain., Botella J; Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain., Juola JF; Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, Madrid, Spain.; Department of Social Psychology, University of Kansas, Lawrence, Kansas, USA.
Jazyk: angličtina
Zdroj: Memory & cognition [Mem Cognit] 2024 May; Vol. 52 (4), pp. 793-825. Date of Electronic Publication: 2024 Jan 04.
DOI: 10.3758/s13421-023-01501-8
Abstrakt: Signal detection theory (SDT) and two-high threshold models (2HT) are often used to analyze accuracy data in recognition memory paradigms. However, when reaction times (RTs) and/or confidence levels (CLs) are also measured, they usually are analyzed separately or not at all as dependent variables (DVs). We propose a new approach to include these variables based on multinomial processing tree models for discrete and continuous variables (MPT-DC) with the aim to compare fits of SDT and 2HT models. Using Juola et al.'s (2019, Memory & Cognition, 47[4], 855-876) data we have found that including CLs and RTs reduces the standard errors of parameter estimates and accounts for interactions among accuracy, CLs, and RTs that classical versions of SDT and 2HT models do not. In addition, according to the simulations, there is an increase in the proportion of correct model selections when relevant DV are included. We highlight the methodological and substantive advantages of MPT-DC in the disentanglement of contributing processes in recognition memory.
(© 2023. The Author(s).)
Databáze: MEDLINE
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