Type and token bigram frequencies for two through nine letter words and the prediction of anagram difficulty

Recent research on anagram solution has produced two original findings. First, it has shown that a new bigram frequency measure called top rank, which is based on a comparison of summed bigram frequencies, is an important predictor of anagram difficulty. Second, it has suggested that the measures from a type count are better than token measures at predicting anagram difficulty. Testing these hypotheses has been difficult because the computation of the bigram statistics is difficult. We present a program that calculates bigram measures for two-to nine-letter words. We then show how the program can be used to compare the contribution of top rank and other bigram frequency measures derived from both a token and a type count. Contrary to previous research, we report that type measures are not better at predicting anagram solution times and that top rank is not the best predictor of anagram difficulty. Lastly we use this program to show that type bigram frequencies are not as good as token bigram frequencies at predicting word identification reaction time.