Modeling the effects of repetition and word frequency in perceptual identification

The counter model for word identification (Ratcliff & McKoon, 1997) has bee n 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 j eopardizing its explanations of the effects on word identification of a lar ge number of other variables.