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, R2. This article proposes a new index—PAND, the “percentage of all non-overlapping data”—to remedy deficiencies of both PND and R2. 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 R2, 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 R2. 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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How special education teachers spend their time is largely unknown. Yet conceptually, “time” is one of the most tangible and salient variables of the effective instruction literature, Carroll's model of school learning and many economic models of performance measures. This currently unknown use of teacher time has clear and important implications for special education research and practice that include teacher quality, the professional roles of educator's, accountability and student achievement. 36 special education teachers representing 4 variations of instructional arrangements recorded 2200 hours of data in the spring of 2006. Special educators reported their time use via a web-based monitoring system while continuous and interval direct observation data were simultaneously collected. Data provide a snapshot view of teacher time use and reflect the percentages of a school day spent in academic instruction, non-academic instruction, instructional support, consultation/collaboration, assessment, planning/preparation, discipline, supervision, paperwork, and other responsibilities throughout the year.