One could easily argue that the most commonly studied stimulus set in experimental psychology involves English words. The study of the memory and reading of words has been central to research since Cattell (1886). Words are well-described units that provide the link between perception and meaning, and so have been critical to developments in computational modeling (e.g., McClelland & Rumelhart, 1981), neuroimaging (e.g., Petersen, Fox, Posner, Mintun, & Raichle, 1989, and conceptions of attention and automaticity (e.g., Neely, 1977;Stroop, 1935), among many other research areas.Given the importance of words as a stimulus set, one might assume that there are relatively straightforward ways to study lexical processing, and that there is a wellconstrained set of findings to which one can appeal in building models of word processing. Although there has been considerable progress in understanding how people process words, there are some clear gaps in the available literature. This paper describes the English Lexicon Project (ELP), which provides a behavioral database for over 40,000 words and nonwords that will help fill some of these gaps. The present description will focus on visual word recognition, although, as described below, the current database has relevance for other aspects of word processing, such as memory and speech production. Before describing the ELP, we will briefly describe the behavioral measures in the database, the limitations in our current knowledge, and how this database will help address these limitations. LEXICAL DECISIONS AND NAMING AS THE BEHAVIORAL TARGETSAlthough there are multiple ways to measure lexical processing (e.g., eye-fixation data, probability of iden- The English Lexicon Project is a multiuniversity effort to provide a standardized behavioral and descriptive data set for 40,481 words and 40,481 nonwords. It is available via the Internet at elexicon.wustl.edu. Data from 816 participants across six universities were collected in a lexical decision task (approximately 3400 responses per participant), and data from 444 participants were collected in a speeded naming task (approximately 2500 responses per participant). The present paper describes the motivation for this project, the methods used to collect the data, and the search engine that affords access to the behavioral measures and descriptive lexical statistics for these stimuli.

Speeded visual word naming and lexical decision performance are reported for 2428 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. imageahility 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, level 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.

Three experiments investigated the impact of five lexical variables (instance dominance, category dominance, word frequency, word length in letters, and word length in syllables) on performance in three different tasks involving word recognition: category verification, lexical decision, and pronunciation. Although the same set of words was used in each task, the relationship of the lexical variables to reaction time varied significantly with the task within which the words were embedded. In particular, the effect of word frequency was minimal in the category verification task, whereas it was significantly larger in the pronunciation task and significantly larger yet in the lexical decision task. It is argued that decision processes having little to do with lexical access accentuate the word-frequency effect in the lexical decision task and that results from this task have questionable value in testing the assumption that word frequency orders the lexicon, thereby affecting time to access the mental lexicon. A simple two-stage model is outlined to account for the role of word frequency and other variables in lexical decision. The model is applied to the results of the reported experiments and some of the most important findings in other studies of lexical decision and pronunciation.

Research on group differences in response latency often has as its goal the detection of Group x Treatment interactions. However, accumulating evidence suggests that response latencies for different groups are often linearly related, leading to an increased likelihood of finding spurious overadditive interactions in which the slower group produces a larger treatment effect. The authors propose a rate-amount model that predicts linear relationships between individuals and that includes global processing parameters based on large-scale group differences in information processing. These global processing parameters may be used to linearly transform response latencies from different individuals to a common information-processing scale so that small-scale group differences in information processing may be isolated. The authors recommend linear regression and z-score transformations that may be used to augment traditional analyses of raw response latencies.

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