A multinomial modeling analysis of the recognition-failure paradigm

The recognition-failure paradigm has received much theoretical consideration, especially the Tulving-Wiseman function and its exceptions. We show that the Tulving-Wiseman function does a poor job of accounting for the data, both when its fit is measured with a model-based, goodness-of-fit statistic and when a logically equivalent reformulation of the function is compared with data. We then present a simple multinomial model based on retrieval-independence theory that is capable of measuring storage and retrieval processes in recognition failure. The model is used to conduct a meta-analysis of the recognition-failure paradigm, and shows that violations of the Tulving-Wiseman function occur under conditions in which weak storage is coupled with strong retrieval. In addition, if storage and retrieval are assumed to be positively correlated across conditions, the model produces a theoretically motivated, alternative equation to the Tulving-Wiseman function that provides a virtually identical fit to the data.