In the following self-paced reading study, we assess the cognitive realism of six widely used corpus-derived measures of association strength between words (collocated modifier–noun combinations like vast majority): MI, MI3, Dice coefficient, T-score, Z-score, and log-likelihood. The ability of these collocation metrics to predict reading times is tested against predictors of lexical processing cost that are widely established in the psycholinguistic and usage-based literature, respectively: forward/backward transition probability and bigram frequency. In addition, the experiment includes the treatment variable of task: it is split into two blocks which only differ in the format of interleaved comprehension questions (multiple choice vs. typed free response). Results show that the traditional corpus-linguistic metrics are outperformed by both backward transition probability and bigram frequency. Moreover, the multiple-choice condition elicits faster overall reading times than the typed condition, and the two winning metrics show stronger facilitation on the critical word (i.e. the noun in the bigrams) in the multiple-choice condition. In the typed condition, we find an effect that is weaker and, in the case of bigram frequency, longer lasting, continuing into the first spillover word. We argue that insufficient attention to task effects might have obscured the cognitive correlates of association scores in earlier research.