MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment

Abstract

The main purpose of this study was to examine the validity of the approach to lexical diversity assessment known as the measure of textual lexical diversity (MTLD). The index for this approach is calculated as the mean length of word strings that maintain a criterion level of lexical variation. To validate the MTLD approach, we compared it against the performances of the primary competing indices in the field, which include vocd-D, TTR, Maas, Yule’s K, and an HD-D index derived directly from the hypergeometric distribution function. The comparisons involved assessments of convergent validity, divergent validity, internal validity, and incremental validity. The results of our assessments of these indices across two separate corpora suggest three major findings. First, MTLD performs well with respect to all four types of validity and is, in fact, the only index not found to vary as a function of text length. Second, HD-D is a viable alternative to the vocd-D standard. And third, three of the indices—MTLD, vocd-D (or HD-D), and Maas—appear to capture unique lexical information. We conclude by advising researchers to consider using MTLD, vocd-D (or HD-D), and Maas in their studies, rather than any single index, noting that lexical diversity can be assessed in many ways and each approach may be informative as to the construct under investigation.