ARI, the Automated
Readability Index, is a function of characters per word and per sentence.
99 As an additional robustness check, we also ran a model (Model 3) that included a single readability measure, ARI (Automated
Readability Index), instead of our readability factor variable.
His readability index is used in Microsoft Word (in the spellcheck function).
He developed
a readability index and authored many books on plain language, including How to Write in Plain English: A Book for Lawyers and Consumers (1979).
Tools such as the Flesch - Kincaid
Readability Index may be utilized when a book is being evaluated for reading grade level.
Calculating an item's «
readability index».
(For a good overview of the history of
readability indexes, see Principles of Readability by William H. DuBay.)
Not exact matches
The late Jeanne Chall and Sue S. Conard studied widely used textbooks covering the period from 1945 to 1975 and noted, «On the whole, the later the copyright dates of the textbooks for the same grade, the easier they were, as measured by
indices of
readability level, maturity level, difficulty of questions, and extent of illustration.»
Those measures, however, rely entirely on two structural features — syllables per word and words per sentence.48 As we describe below, we have adopted a comprehensive approach to measuring
readability by taking fifty different
readability measures and then using factor analysis to create an
index based on the most reliable set of measures.49 The next section discusses the few prior studies of the relationship between
readability and case outcome.
For example, Feldman analyzed the quality of Supreme Court merits briefs using a composite of features such as passivity, wordiness, sentence length, and tone.63 He found that brief
readability was positively associated with the percentage of brief language adopted in the opinion and that the association was highly significant.64 Similarly, Collins et al. analyzed the «cognitive clarity» and plain language of Supreme Court amicus briefs.65 They measured cognitive clarity using the dictionary - based Linguistic Inquiry and Word Count program (LIWC), which relied on an
index of categories that relate to cognitive clarity such as «causation, insight, discrepancy, inhibition, tentativeness, certainty, exclusiveness, inclusiveness, negations, and the percentage of words containing six or more letters.»
The study measured
readability using the Gunning Fog
Index, which generates a
readability score based on the number of words per sentence and the frequency of complex words.