The effects of word length on visual word recognition have been examined with a variety of techniques (such as perceptual identification, lexical decision, naming, eye tracking), but the results have been inconsistent, ranging from inhibitory (longer words are harder) to null effects. Word length can be based on orthographic measures (number of letters) or phonological measures (number of phonemes and syllables). These different measures are generally highly intercorrelated, and they also correlate with other variables (such as the number of orthographic neighbors and the printed frequency) that influence word recognition. In the present study, we are primarily interested in word length as measured by the number of letters. Early Studies Using Perceptual Identification Perceptual identification was the main dependent variable in the first studies of visual word recognition. Some of these studies included word length as an independent variable. As can been seen in Table 1, these experiments yielded a mixture of null effects and inhibitory length effects. A problem with the perceptual identification task, however, is that interpretation of the data is difficult. Because of the offline nature of the dependent variable (percentage of words recognized), participants may have tried to guess the word on the basis of the few letters they were able to identify. As a result, perceptual identification was progressively abandoned in favor of tasks measuring online processing (Monsell, 1991). More Recent Studies Using Tasks Recording Online Reaction Times More recent studies using online reaction times, such as those obtained in lexical decision, naming, and eye movement recording, have also reported mixed results (again see Table 1). Hudson and Bergman (1985), for example, obtained reliable inhibitory length effects for words with 4-12 letters in naming (the size of the effect was 3.2 msec 45 In the present study, we reexamined the effect of word length (number of letters in a word) on lexical decision. Using the English Lexicon Project, which is based on a large data set of over 40,481 words (Balota et al., 2002), we performed simultaneous multiple regression analyses on a selection of 33,006 English words (ranging from 3 to 13 letters in length). Our analyses revealed an unexpected pattern of results taking the form of a U-shaped curve. The effect of number of letters was facilitatory for words of 3-5 letters, null for words of 5-8 letters, and inhibitory for words of 8-13 letters. We also showed that printed frequency, number of syllables, and number of orthographic neighbors all made independent contributions. The length effects were replicated in a new analysis of a subset of 3,833 monomorphe-mic nouns (ranging from 3 to 10 letters), and also in another analysis based on 12,987 bisyllabic items (ranging from 3 to 9 letters). These effects were independent of printed frequency, number of syllables, and number of orthographic neighbors. Furthermore, we also observed robust linear inhibitory effects of number of syllables. Implications for models of visual word recognition are discussed.