Evaluating parameter recovery of subject level parameters in the memory measurement model framework

The memory measurement model (M3; Oberauer & Lewandowsky, 2018) is a cognitive measurement model designed to isolate parameters associated with different processes in working memory. It assumes that different categories of representations in working memory get activated through distinct processes. Transforming the activation of the different item categories into their respective recall probabilities then allows to estimate the contributions of different memory processes to working memory performance. So far, parameter recovery was assessed only for group level parameters of the M3. In contrast to experimental research, individual differences research relies on variation in subject parameters. The quality of parameter recovery of subject parameters has, however, not yet been investigated. To analyze parameter recovery of subject parameters of the M3, we ran a parameter recovery simulation to assess the model performance in recovering subject-level parameters dependent on different experimental conditions. In this talk, we will present the results of this parameter recovery study that used a multivariate parametrization of the model implemented in STAN using the no-u-turn sampler (Hoffman & Gelman, 2011). The results of the simulation indicate that our implementation of the M3 recovers subject parameters acceptably. Based on differences between experimental conditions, we will provide recommendations for using the M3 in individual differences research. Altogether, our parameter recovery study showed that the M3 is easily scalable to different experimental paradigms with sufficient recovery performance.