Participants in associative-recognition tasks are shown word pairs to study, and later, in a test, are shown intact or re-arranged word pairs. Mixture SDT models for associative-recognition tasks can be motivated by considering the effects of attention on each trial, as has previously been done for recognition memory, source recognition, and the mirror effect. It is shown that a mixture SDT model proposed for source recognition tasks (DeCarlo, 2003) can be applied to associative-recognition tasks. A unique aspect of the associative-recognition task is that re-arranged word pairs consist of two words, either or both of which might provide some associative information - even if one doesn't remember the word pair (or the pair is not familiar), one may feel confident that one of the words was not paired with the other. Thus, in the model presented here, re-arranged word pairs are viewed as providing associative information. Analysis of recent data suggests that there is indeed associative strength for re-arranged word pairs, but it appears to be smaller than that for intact pairs. The use of new-word pairs, or lures, also raises some interesting questions. For example, new word pairs in associative-recognition tasks might provide information about association: if one is confident that a word is new, then one can also be confident that it was not in a previously presented word pair. Models that incorporate lures and other extensions are considered. |