The Michigan Corpus of Upper-Level Student Papers (MICUSP) contains 828 student papers. Here each document is tagged with Biber features using the pseudobibeR package. Type-to-token ratio is calculated using the moving average type-to-token ratio (MATTR).
micusp_biberA data frame with 828 rows and 68 columns:
Document ID (from MICUSP)
Rate of past tense per 1,000 tokens
Rate of perfect aspect per 1,000 tokens
Rate of present tense per 1,000 tokens
Rate of place adverbials per 1,000 tokens
Rate of time adverbials per 1,000 tokens
Rate of first person pronouns per 1,000 tokens
Rate of second person pronouns per 1,000 tokens
Rate of third person pronouns per 1,000 tokens
Rate of pronoun 'it' per 1,000 tokens
Rate of demonstrative pronouns per 1,000 tokens
Rate of indefinite pronouns per 1,000 tokens
Rate of proverb 'do' per 1,000 tokens
Rate of wh-questions per 1,000 tokens
Rate of nominalizations per 1,000 tokens
Rate of gerunds per 1,000 tokens
Rate of other nouns per 1,000 tokens
Rate of agentless passives per 1,000 tokens
Rate of by-passives per 1,000 tokens
Rate of 'be' as main verb per 1,000 tokens
Rate of existential 'there' per 1,000 tokens
Rate of that-verb complements per 1,000 tokens
Rate of that-adjective complements per 1,000 tokens
Rate of wh-clauses per 1,000 tokens
Rate of infinitives per 1,000 tokens
Rate of present participles per 1,000 tokens
Rate of past participles per 1,000 tokens
Rate of past participle whiz-deletions per 1,000 tokens
Rate of present participle whiz-deletions per 1,000 tokens
Rate of that-subject clauses per 1,000 tokens
Rate of that-object clauses per 1,000 tokens
Rate of wh-subject clauses per 1,000 tokens
Rate of wh-object clauses per 1,000 tokens
Rate of pied-piping per 1,000 tokens
Rate of sentence relatives per 1,000 tokens
Rate of 'because' per 1,000 tokens
Rate of 'though' per 1,000 tokens
Rate of 'if' per 1,000 tokens
Rate of other adverbial subordinators per 1,000 tokens
Rate of prepositions per 1,000 tokens
Rate of attributive adjectives per 1,000 tokens
Rate of predicative adjectives per 1,000 tokens
Rate of adverbs per 1,000 tokens
Type-token ratio (MATTR)
Mean word length
Rate of conjuncts per 1,000 tokens
Rate of downtoners per 1,000 tokens
Rate of hedges per 1,000 tokens
Rate of amplifiers per 1,000 tokens
Rate of emphatics per 1,000 tokens
Rate of discourse particles per 1,000 tokens
Rate of demonstratives per 1,000 tokens
Rate of possibility modals per 1,000 tokens
Rate of necessity modals per 1,000 tokens
Rate of predictive modals per 1,000 tokens
Rate of public verbs per 1,000 tokens
Rate of private verbs per 1,000 tokens
Rate of suasive verbs per 1,000 tokens
Rate of 'seem' verbs per 1,000 tokens
Rate of contractions per 1,000 tokens
Rate of that-deletions per 1,000 tokens
Rate of stranded prepositions per 1,000 tokens
Rate of split infinitives per 1,000 tokens
Rate of split auxiliaries per 1,000 tokens
Rate of phrasal coordination per 1,000 tokens
Rate of clausal coordination per 1,000 tokens
Rate of synthetic negation per 1,000 tokens
Rate of analytic negation per 1,000 tokens