Measurement models for visual working memory-A factorial model comparison

Several measurement models have been proposed for data from the continuous-reproduction paradigm for studying visual working memory (WM): The original mixture model (Zhang & Luck, 2008) and its extension (Bays et al., 2009); the interference measurement model (IMM; Oberauer et al., 2017), and the target confusability competition (TCC) model (Schurgin et al., 2020). This article describes a space of possible measurement models in which all these models can be placed. The space is defined by three dimensions: (a) The choice of an activation function (von-Mises or Laplace), (b) the choice of a response-selection function (variants of Luce's choice rule or of signal-detection theory), (c) and whether or not memory precision is assumed to be a constant over manipulations affecting memory. A factorial combination of these three variables generates all possible models in the model space. Fitting all models to eight data sets revealed a new model as empirically most adequate, which combines a von-Mises activation function with a signal-detection response-selection rule. The precision parameter can be treated as a constant across many experimental manipulations, though it probably varies between individuals. All modeling code and the raw data modeled are available on the OSF: https://osf.io/zwprv/ (PsycInfo Database Record (c) 2023 APA, all rights reserved).