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M J Cortese

Publications and source records attributed to M J Cortese.

2 recordsLinked to original sources

Subjective frequency estimates for 2,938 monosyllabic words.

Subjective frequency estimates for large sample of monosyllabic English words were collected from 574 young adults (undergraduate students) and from a separate group of 1,590 adults of varying ages and educational backgrounds. Estimates from the latter group were collected via the internet. In addition, 90 healthy older adults provided estimates for a random sample of 480 of these words. All groups rated words with respect to the estimated frequency of encounters of each word on a 7-point scale, ranging from never encountered to encountered several times a day. The young and older groups also rated each word with respect to the frequency of encounters in different perceptual domains (e.g., reading, hearing, writing, or speaking). The results of regression analyses indicated that objective log frequency and meaningfulness accounted for most of the variance in subjective frequency estimates, whereas neighborhood size accounted for the least amount of variance in the ratings. The predictive power of log frequency and meaningfulness were dependent on the level of subjective frequency estimates. Meaningfulness was a better predictor of subjective frequency for uncommon words, whereas log frequency was a better predictor of subjective frequency for common words. Our discussion focuses on the utility of subjective frequency estimates compared with other estimates of familiarity. The raw subjective frequency data for all words are available at http://www.artsci.wustl.edu/dbalota/labpub.html.

Adolescent↗

Regularity effects in word naming: what are they?

In a word-naming experiment, word-body consistency was crossed with grapheme-to-phoneme regularity to test predictions of current models of word recognition. In the latency and error data, a clear effect of consistency was observed, with the influence of regularity somewhat weaker. In addition, simulation data from three contemporary models of word recognition were obtained for the stimuli used in the experiment in order to compare the models' latencies with those of humans. The simulations showed that the human latency data are most consistent with the parallel-distributed-processing model of Plaut, McClelland, Seidenberg, and Patterson (1996), less so with the dual-process model (Zorzi, Houghton, & Butterworth, 1998), and least so with the dual-route-cascaded model (Coltheart & Rastle, 1994).

Adult↗