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Studies using video analysis are being reported more frequently in the literature. Although the body of research suggests that video analysis is effective for changing educators' instructional practices, questions regarding for whom and under what circumstances it is most effective still remain. This meta-analysis reports on the overall effectiveness of video analysis when used with special educators, as well as on moderator analyses related to participant and instructional characteristics. Tau-U, a nonparametric effect size commonly used in single-case research, was used to aggregate the results from 191 AB phase contrasts across 12 dissertations and 18 peer-reviewed publications. A total of 111 participants across 69 single-case design experiments are reflected in the results. Overall, results indicate that video analysis is effective for changing the instructional practices of special educators and that it can be used across a variety of settings and with a diverse group of educators. [ABSTRACT FROM AUTHOR]

Momentary time sampling (MTS), whole interval recording (WIR), and partial interval recording (PIR) are commonly used in applied research. We discuss potential difficulties with analyzing data when these systems are used and present results from a pilot simulation study designed to determine the extent to which these issues are likely to be problematic in the context of single case design studies. Results indicate that WIR and PIR may result in invalid effect size estimations. Although MTS more closely paralleled actual duration, it may induce variability in relatively short sessions, increasing the likelihood of Type II errors. Suggestions for practitioners, consumers, and researchers include careful use and reporting of data collected using interval-based systems and continued investigation of properties of these systems, particularly on the effects on effect size estimations. [ABSTRACT FROM AUTHOR]

Nonoverlap is widely used as a statistical summary of data; however, these analyses rarely correct unwanted positive baseline trend. This article presents and validates the graph rotation for overlap and trend (GROT) technique, a hand calculation method for controlling positive baseline trend within an analysis of data nonoverlap. GROT is validated for controlling positive baseline trend and validated socially by visual analysis agreement. The flexibility and generality of GROT is demonstrated by using it with two alternative slope calculations: White and Haring’s bi-split and Tukey’s tri-split. In addition, GROT is presented as a technique that can be adapted for any non-overlap effect size method; examples here include the original percent of nonoverlapping data and newer nonoverlap of all pairs. examples here include the original percent of nonoverlapping data and newer nonoverlap of all pairs. Caution is urged to control baseline trend only when it is pronounced and reliable. GROT moves the field forward as a robust technique suitable for both visual and statistical analysis. [ABSTRACT FROM PUBLISHER]

The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD’s utility centers on three issues: sample size, effect size, and serial dependence. One potential method for addressing all three issues is hierarchical linear modeling (HLM) meta-analysis. This study explored the utility of HLM meta-analysis of SSD. A total of 206 functional behavior assessment–based intervention outcome graphs were aggregated to assess whether HLM meta-analysis could identify (a) an overall effect size and statistical significance for mean shift, slope, and variability; (b) how the results mapped to two additional effect size calculations; and (c) whether the procedure met SSD synthesis criteria outlined by Wolery, Busick, Reichow, and Barton. [ABSTRACT FROM PUBLISHER]