Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity

Contextual diversity modifies word frequency by ignoring the repetition of words in context (Adelman, Brown, & Quesada, 2006 , Psychological Science, 17 (9) , 814–823). Semantic diversity modifies contextual diversity by taking into account the uniqueness of the contexts that a word occurs in when calculating lexical strength (Jones, Johns, & Recchia, 2012 , Canadian Journal of Experimental Psychology, 66, 115–124). Recent research has demonstrated that measures based on contextual and semantic diversity provide a considerable improvement over word frequency when accounting for lexical organization data (Johns, 2021 , Psychological Review, 128, 525–557; Johns, Dye, & Jones, 2020a , Quarterly Journal of Experimental Psychology, 73, 841–855). The article demonstrates that these same findings generalize to word-level episodic recognition rates, using the previously released data of Cortese, Khanna, and Hacker (Cortese et al., 2010 , Memory , 18, 595–609) and Cortese, McCarty, and Schock (Cortese et al., 2015 , Quarterly Journal of Experimental Psychology , 68, 1489–1501). It was found that including the best fitting contextual diversity model allowed for a very large increase in variance accounted for over previously used variables, such as word frequency, signalling commonality with results from the lexical organization literature. The findings of this article suggest that current trends in the collection of megadata sets of human behavior (e.g., Balota et al., 2007 , Behavior Research Methods, 39 (3) , 445–459) provide a promising avenue to develop new theoretically oriented models of word-level episodic recognition data.