Tau-U: A Quantitative Approach for Analysis of Single-Case Experimental Data in Aphasia

Am J Speech Lang Pathol. 2018 Mar 1;27(1S):495-503. doi: 10.1044/2017_AJSLP-16-0197.

Abstract

Purpose: Tau-U is a quantitative approach for analyzing single-case experimental design (SCED) data. It combines nonoverlap between phases with intervention phase trend and can correct for a baseline trend (Parker, Vannest, & Davis, 2011). We demonstrate the utility of Tau-U by comparing it with the standardized mean difference approach (Busk & Serlin, 1992) that is widely reported within the aphasia SCED literature.

Method: Repeated writing measures from 3 participants with chronic aphasia who received computer-based writing treatment are analyzed visually and quantitatively using both Tau-U and the standardized mean difference approach.

Results: Visual analysis alone was insufficient for determining an effect between the intervention and writing improvement. The standardized mean difference yielded effect sizes ranging from 4.18 to 26.72 for trained items and 1.25 to 3.20 for untrained items. Tau-U yielded significant (p < .05) effect sizes for 2 of 3 participants for trained probes and 1 of 3 participants for untrained probes. A baseline trend correction was applied to data from 2 of 3 participants.

Conclusions: Tau-U has the unique advantage of allowing for the correction of an undesirable baseline trend. Although further study is needed, Tau-U shows promise as a quantitative approach to augment visual analysis of SCED data in aphasia.

Publication types

  • Randomized Controlled Trial
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aphasia / diagnosis
  • Aphasia / psychology
  • Aphasia / therapy*
  • Data Interpretation, Statistical
  • Female
  • Humans
  • Language Therapy / methods
  • Language Therapy / statistics & numerical data*
  • Male
  • Memory
  • Middle Aged
  • Reading*
  • Recovery of Function
  • Research Design / statistics & numerical data*
  • Statistics, Nonparametric
  • Therapy, Computer-Assisted / methods
  • Therapy, Computer-Assisted / statistics & numerical data*
  • Treatment Outcome
  • Writing*