title: Automated Proposition Density Analysis for Discourse in Aphasia.
abstract: This study evaluates how proposition density can differentiate between persons with aphasia (PWA) and individuals in a control group, as well as among subtypes of aphasia, on the basis of procedural discourse and personal narratives collected from large samples of participants.
  
  
  
  Participants were 195 PWA and 168 individuals in a control group from the AphasiaBank database. PWA represented 6 aphasia types on the basis of the Western Aphasia Battery-Revised (Kertesz, 2006). Narrative samples were stroke stories for PWA and illness or injury stories for individuals in the control group. Procedural samples were from the peanut-butter-and-jelly-sandwich task. Language samples were transcribed using Codes for the Human Analysis of Transcripts (MacWhinney, 2000) and analyzed using Computerized Language Analysis (MacWhinney, 2000), which automatically computes proposition density (PD) using rules developed for automatic PD measurement by the Computerized Propositional Idea Density Rater program (Brown, Snodgrass, & Covington, 2007; Covington, 2007).
  
  
  
  Participants in the control group scored significantly higher than PWA on both tasks. PD scores were significantly different among the aphasia types for both tasks. Pairwise comparisons for both discourse tasks revealed that PD scores for the Broca's group were significantly lower than those for all groups except Transcortical Motor. No significant quadratic or linear association between PD and severity was found.
  
  
  
  Proposition density is differentially sensitive to aphasia type and most clearly differentiates individuals with Broca's aphasia from the other groups.
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Davida
authors.initials: D
authors.lastname: Fromm
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Joel
authors.initials: J
authors.lastname: Greenhouse
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Kaiyue
authors.initials: K
authors.lastname: Hou
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: G Austin
authors.initials: GA
authors.lastname: Russell
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Xizhen
authors.initials: X
authors.lastname: Cai
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Margaret
authors.initials: M
authors.lastname: Forbes
authors.affiliation: University of Arizona, Tucson.
authors.forename: Audrey
authors.initials: A
authors.lastname: Holland
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Brian
authors.initials: B
authors.lastname: MacWhinney
mesh_terms: D000368:Aged; D001037:Aphasia / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D007807:Language Tests; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D033262:Narration; D010363:Pattern Recognition, Automated; D013060:Speech