Q: In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
Meaningfully synthesizing single case experimental data from intervention studies comprised of individuals with low incidence conditions and generating effect size estimates remains challenging. Seven effect size metrics were compared for single case design (SCD) data focused on teaching speech generating device use to individuals with intellectual and developmental disabilities (IDD) with moderate to profound levels of impairment. The effect size metrics included percent of data points exceeding the median (PEM), percent of nonoverlapping data (PND), improvement rate difference (IRD), percent of all nonoverlapping data (PAND), Phi, nonoverlap of all pairs (NAP), and Tau novlap . Results showed that among the seven effect size metrics, PAND, Phi, IRD, and PND were more effective in quantifying intervention effects for the data sample (N = 285 phase or condition contrasts). Results are discussed with respect to issues concerning extracting and calculating effect sizes, visual analysis, and SCD intervention research in IDD. effect size metric; speech generating devices; single case design; intellectual and developmental disabilities; evidence-based practices Evidence-based practice (EBP) has become a standard for an increasing number of educational and human services disciplines (American Speech-Language-Hearing domains of applied research, meta-analyses can be more challenging to implement because of the lack of agreed upon effect size metrics (Lipsey & Wilson, 2001; Shadish, Hedges, & Pustejovsky, 2014) . One area where this is particularly evident involves intervention research with low-incidence populations including individuals with intellectual and developmental disabilities (IDD) with moderate to profound levels of impairment. In the specific area of speech generating device (SGD) interventions for individuals with IDD with moderate to profound levels of impairment, for example, the population is extremely heterogeneous. This has resulted in a preponderance of single case design (SCD) studies for which there is not a standard effect size metric. In this article, we used the results from SCD SGD intervention studies as a vehicle to further evaluate different non-parametric effect size metrics from SCD studies. Our rationale was, in part, pragmatic. That is, the literature specific to SGD and severe disabilities is a manageable literature. Additionally, SGDs represent an area of a relatively rapid growth with tablet-based systems emerging and proliferating (Kuster, 2012; McNaughton & Light, 2013) . In the following sections we provide a brief overview of the literature addressing SGD and SCD. Subsequently, we provide a rationale for the SCD effect size comparisons that were conducted.
A:
Comparing Single Case Design Overlap-Based Effect Size Metrics From Studies Examining Speech Generating Device Interventions HHS Public Access The Need for Effect Size Clarity for Applied Intervention Research With Low-Incidence Populations Using SGDs