Visual word recognition of single-syllable words

Speeded visual word naming and lexical decision performance are reported for 2,428 words for young adults and healthy older adults. Hierarchical regression techniques were used to investigate the unique predictive variance of phonological features in the onsets, lexical variables (e.g., measures of consistency, frequency, familiarity, neighborhood size, and length), and semantic variables (e.g., imageability and semantic connectivity). The influence of most variables was highly task dependent, with the results shedding light on recent empirical controversies in the available word recognition literature. Semantic-level variables accounted for unique variance in both speeded naming and lexical decision performance, with the latter task producing the largest semantic-level effects. Discussion focuses on the utility of large-scale regression studies in providing a complementary approach to the standard factorial designs to investigate visual word recognition. The study of the processes involved in isolated word recognition has been central to developments in experimental psychology since the days of Cattell (1886). Researchers have accumulated a vast amount of information regarding the statistical properties of words, including word frequency, subjective familiarity, meaning-fulness, letter frequency, bigram frequency, trigram frequency, spelling-to-sound consistency, syntactic class, and concreteness (see Balota, 1994, and Henderson, 1982, for reviews). Word rec-ognition research has been critical in developing computational models (e.g., Coltheart, Curtis, Atkins, & Haller, 1993; McClel