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ERIC Number: EJ758186
Record Type: Journal
Publication Date: 2007
Pages: 11
Abstractor: Author
Reference Count: 0
ISSN: ISSN-0022-4669
Percentage of All Non-Overlapping Data (PAND): An Alternative to PND
Parker, Richard I.; Hagan-Burke, Shanna; Vannest, Kimberly
Journal of Special Education, v40 n4 p194-204 Win 2007
Although single-case researchers are not accustomed to analyzing data statistically, standards for research and accountability from government and other funding agents are creating pressure for more objective, reliable data. In addition, "evidence-based interventions" movements in special education, clinical psychology, and school psychology imply reliable data summaries. Within special education, two heavily debated single-case research (SCR) statistical indices are "percentage of non-overlapping data" (PND) and the regression effect size, R[squared]. This article proposes a new index--PAND, the "percentage of all non-overlapping data"--to remedy deficiencies of both PND and R[squared]. PAND is closely related to the established effect size, Pearson's "Phi", the "fourfold point correlation coefficient." The PAND/"Phi" procedure is demonstrated and applied to 75 published multiple baseline designs to answer questions about typical effect sizes, relationships with PND and R[squared], statistical power, and time efficiency. Confidence intervals and p values for "Phi" also are demonstrated. The findings are that PAND/"Phi" and PND correlate equally well to R[squared]. However, only PAND/"Phi" could show adequate power for most of the multiple baseline designs sampled. The findings suggest that PAND/"Phi" may meet the requirement for a useful effect size for multiple baseline and other longer designs in SCR.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A