Reliability of multi-category rating scales.

The use of multi-category scales is increasing for the monitoring of IEP goals, classroom and school rules, and Behavior Improvement Plans (BIPs). Although they require greater inference than traditional data counting, little is known about the inter-rater reliability of these scales. This simulation study examined the performance of nine reliability indices applied to six multi-category scales of different gradations (2, 3, 5, 7, 10, and 15 points) all derived from the same quasi-continuous (1-30) data.

Moderating factors of video-modeling with other as model: a meta-analysis of single-case studies.

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not previously been explored. The purpose of this study was to meta-analytically evaluate the evidence base of VMO with individuals with disabilities to determine if participant characteristics and targeted outcomes moderate the effectiveness of the intervention.

Combining nonoverlap and trend for single-case research: Tau-U.

A new index for analysis of single-case research data was proposed, Tau-U, which combines nonoverlap between phases with trend from within the intervention phase. In addition, it provides the option of controlling undesirable Phase A trend. The derivation of Tau-U from Kendall's Rank Correlation and the Mann-Whitney U test between groups is demonstrated.

Robust regression for single-case data analysis: how can it help?

This study examined the degree to which outliers were present in a convenience sample of published single-case research. Using a procedure for analyzing single-case data Allison & Gorman (Behaviour Research and Therapy, 31, 621-631, 1993), this study compared the effect of outliers using ordinary least squares (OLS) regression to a robust regression method and attempted to answer four questions: (1) To what degree does outlier detection vary from OLS to robust regression? (2) How much do effect sizes differ from OLS to robust regression? (3) Are the differences produced by robust regression in more or less agreement with visual judgments of treatment effectiveness? (4) What is a typical range of effect sizes for robust regression versus OLS regression for data from "effective interventions"? Results suggest that outliers are common in single-case data. The effects of outliers in single-case data are explored, and the implications for researchers and practitioners using single-case designs are discussed.

Effect size in single-case research: a review of nine nonoverlap techniques.

With rapid advances in the analysis of data from single-case research designs, the various behavior-change indices, that is, effect sizes, can be confusing. To reduce this confusion, nine effect-size indices are described and compared. Each of these indices examines data nonoverlap between phases.

A meta-analysis of single case research studies on aided augmentative and alternative communication systems with individuals with autism spectrum disorders.

Many individuals with autism cannot speak or cannot speak intelligibly. A variety of aided augmentative and alternative communication (AAC) approaches have been investigated. Most of the research on these approaches has been single-case research, with small numbers of participants.

An improved effect size for single-case research: nonoverlap of all pairs.

Nonoverlap of All Pairs (NAP), an index of data overlap between phases in single-case research, is demonstrated and field tested with 200 published AB contrasts. NAP is a novel application of an established effect size known in various forms as Area Under the Curve (AUC), the Common Language Effect Size (CL), the Probability of Superiority (PS), the Dominance Statistic (DS), Mann-Whitney's U, and Sommers D, among others. NAP was compared with 3 other non-overlap-based indices: PND (percent of nonoverlapping data), PEM (percent of data points exceeding the median), and PAND (percent of all nonoverlapping data), as well as Pearson's R(2).

Median-based overlap analysis for single case data: a second study.

This article takes a further look at the percentage of data points exceeding the median (PEM) analysis method for single-case research data, first presented in this journal by Hsen-Hsing Ma. Ma examined the relationship between PEM and the established percentage of nonoverlapping data (PND) and then applied PEM in a meta-analysis of 61 data sets, correlating their authors' judgments of intervention effectiveness with PEM. The present article covers PEM's historical and statistical context and then applies the new measure in a field test with 165 contrasts between a baseline phase A and a treatment phase B.

Useful effect size interpretations for single case research.

An obstacle to broader acceptability of effect sizes in single case research is their lack of intuitive and useful interpretations. Interpreting Cohen's d as "standard deviation units difference" and R2 as "percent of variance accounted for" do not resound with most visual analysts. In fact, the only comparative analysis widely supported in single case research (SCR) is "percent of nonoverlapping data.

Increased reliability for single-case research results: is the bootstrap the answer?

There is need for objective and reliable single-case research (SCR) results in the movement toward evidence-based interventions (EBI), for inclusion in meta-analyses, and for funding accountability in clinical contexts. Yet SCR deals with data that often do not conform to parametric data assumptions and that yield results of low reliability. A resampling technique, the bootstrap, largely bypasses statistical assumptions and usually yields more reliable results.

The relationship between visual analysis and five statistical analyses in a simple AB single-case research design.

This study explored some practical issues for single-case researchers who rely on visual analysis of graphed data, but who also may consider supplemental use of promising statistical analysis techniques. The study sought to answer three major questions: (a) What is a typical range of effect sizes from these analytic techniques for data from "effective interventions"? (b) How closely do results from these same analytic techniques concur with visual-analysis-based judgments of effective interventions? and (c) What role does autocorrelation play in interpretation of these analytic results? To answer these questions, five analytic techniques were compared with the judgments of 45 doctoral students and faculty, who rated intervention effectiveness from visual analysis of 35 fabricated AB design graphs. Implications for researchers and practitioners using single-case designs are discussed.

Solution-focused family therapy with three aggressive and oppositional-acting children: an N = 1 empirical study.

The efficacy of Solution-Focused Family Therapy (SFFT) for helping three families with aggressive and oppositional-acting children (aged 8-9) was examined. The N = 1 multiple-baseline design with three replications used validated measures, a treatment manual, and a treatment integrity measure. The interventions lasted from four to five sessions.