Type-based bigram frequencies for five-letter words.

Abstract

Researchers often require subjects to make judgments that call upon their knowledge of the orthographic structure of English words. Such knowledge is relevant in experiments on, for example, reading, lexical decision, and anagram solution. One common measure of orthographic structure is the sum of the frequencies of consecutive bigrams in the word. Traditionally, researchers have relied on token-based norms of bigram frequencies. These norms confound bigram frequency with word frequency because each instance (i.e., token) of a particular word in a corpus of running text increments the frequencies of the bigrams that it contains. In this article, the authors report a set of type-based bigram frequencies in which each word (i.e., type) contributes only once, thereby unconfounding bigram frequency from word frequency. The authors show that type-based bigram frequency is a better predictor of the difficulty of anagram solution than is token-based frequency. These norms can be downloaded from www.psychonomic.org/archive/.