Modeling the effects of repetition and word frequency in perceptual identification

The counter model for word identification (Ratcliff & McKoon, 1997) has been challenged by recent empirical findings that performance on low-frequency words improves as the result of repetition of the words. We show that the model can accommodate this learning effect, and that it can do so without jeopardizing its explanations of the effects on word identification of a large number of other variables.