• Medientyp: E-Artikel
  • Titel: Assessment of Reliable Change Using 95% Credible Intervals for the Differences in Proportions: A Statistical Analysis for Case-Study Methodology
  • Beteiligte: Unicomb, Rachael; Colyvas, Kim; Harrison, Elisabeth; Hewat, Sally
  • Erschienen: American Speech Language Hearing Association, 2015
  • Erschienen in: Journal of Speech, Language, and Hearing Research
  • Sprache: Englisch
  • DOI: 10.1044/2015_jslhr-s-14-0158
  • ISSN: 1092-4388; 1558-9102
  • Schlagwörter: Speech and Hearing ; Linguistics and Language ; Language and Linguistics
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  • Beschreibung: <jats:sec> <jats:title>Purpose</jats:title> <jats:p>Case-study methodology studying change is often used in the field of speech-language pathology, but it can be criticized for not being statistically robust. Yet with the heterogeneous nature of many communication disorders, case studies allow clinicians and researchers to closely observe and report on change. Such information is valuable and can further inform large-scale experimental designs. In this research note, a statistical analysis for case-study data is outlined that employs a modification to the Reliable Change Index (Jacobson &amp; Truax, 1991). The relationship between reliable change and clinical significance is discussed. Example data are used to guide the reader through the use and application of this analysis.</jats:p> </jats:sec> <jats:sec> <jats:title>Method</jats:title> <jats:p>A method of analysis is detailed that is suitable for assessing change in measures with binary categorical outcomes. The analysis is illustrated using data from one individual, measured before and after treatment for stuttering.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The application of this approach to assess change in categorical, binary data has potential application in speech-language pathology. It enables clinicians and researchers to analyze results from case studies for their statistical and clinical significance. This new method addresses a gap in the research design literature, that is, the lack of analysis methods for noncontinuous data (such as counts, rates, proportions of events) that may be used in case-study designs.</jats:p> </jats:sec>