The Impact of Baseline Trend Control on Visual Analysis of Single-Case Data

Mercer, Sterett H.; Sterling, Heather E.

doi:10.1016/j.jsp.2011.11.004

Cited by 25 publications

(12 citation statements)

References 23 publications

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“…In other words, studies reporting IRA via correlational measures or evaluating the variability around the mean were excluded (i.e., Brossart, Parker, Olson, & Mahadevan, 2006;DeProspero & Cohen, 1979;Jones et al, 1978;Mercer & Sterling, 2012). Proportion of IRA calculations was included because the majority of studies used this computation or provided sufficient information to compute it.…”

Section: Gate 3 Criteria: Computation Screeningmentioning

confidence: 99%

Interrater Agreement Between Visual Analysts of Single-Case Data

et al. 2015

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Visual analysis is the most widely applied method of data interpretation for single-case research as it encompasses multifaceted considerations relevant to evaluating behavior change. However, a previous research synthesis found low levels of interrater agreement between visually analyzed ratings of graphed data across all variables under analysis. The purpose of this meta-analysis was to evaluate the peer-reviewed literature to date for potential moderators affecting the proportion of interrater agreement between visual analysts. Nineteen articles with 32 effects were assembled. Potential moderators evaluated included (a) design families, (b) rater expertise, (c) the provision of contextual information for graphs, (d) the use of visual aids, (e) the provision of an operational definition of the construct being rated, and (f) rating scale ranges. Results yielded an overall weighted interrater agreement proportion of .76. Moderator variables identified produced low to adequate levels of interrater agreement. Practical recommendations for future research are discussed.

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Section: Gate 3 Criteria: Computation Screeningmentioning

confidence: 99%

Interrater Agreement Between Visual Analysts of Single-Case Data

et al. 2015

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“…This problem is due in part to a general lack of guidance as to what constitutes expected responsiveness to various interventions and the absence of agreed upon decision rules for when to make progress-monitoring or instructional changes (Ardoin et al, 2013). In the absence of such guidelines, educators often make decisions on the basis of visual analysis, which can be unreliable with single-case data of a developmental nature (DeProspero & Cohen, 1979; Harbst, Ottenbacher, & Harris, 1991; Mercer & Sterling, 2012; Ottenbacher, 1990; Park, Marascuilo, & Gaylord-Ross, 1990; Van Norman & Christ, 2016b). Another contributing factor is that the residual error—the SEE—surrounding the regression line varies based on the quality of the probes employed (Ardoin & Christ, 2009).…”

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confidence: 99%

Decision-Making Accuracy of CBM Progress-Monitoring Data

Hintze

Wells

Marcotte

et al. 2017

Journal of Psychoeducational Assessment

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This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading growth of twoword increase per week across 15 consecutive weeks. Results indicated that an unacceptably high proportion of cases were falsely identified as nonresponsive to intervention when a common 4-point decision rule was applied, under the context of typical levels of probe reliability. As reliability and stringency of the decision-making rule increased, such errors decreased. Findings are particularly relevant to those who use a multi-tiered response-to-intervention model for evaluating formative changes associated with instructional intervention and evaluating responsiveness to intervention across multiple tiers of intervention. Keywords assessment of interventions/outcomes, diagnostic classification models, measurement, response to intervention (RTI)/multi-tiered system of supports (MTSS), statistical analyses, measurement Curriculum-based measurement (CBM) is a set of standardized and specific measurement procedures that can be used to index student performance in the basic skill areas of early literacy and reading, early numeracy and mathematics computation and application, spelling, and written expression (

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“…At this time, visual analysis remains the gold standard for the interpretation of single-case research. Yet, research has noted difficulties associated with the derivation of valid visual analyses of SCD data, indicating the need for advanced training and understanding of appropriate interpretive guidelines, such as controlling for a trend in baseline data (Knapp 1983;Mercer and Sterling 2012). Partly in recognition of these findings, recent research has targeted the development of methods for the statistical analysis of graphed data.…”

Section: Discussionmentioning

confidence: 99%

Applied Empiricism: Ensuring the Validity of Causal Response to Intervention Decisions

Kilgus

Collier‐Meek

Johnson

et al. 2014

Contemp School Psychol

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School personnel make a variety of decisions within multitiered problem-solving frameworks, including the decision to assign a student to group-based support, to design an individualized support plan, or classify a student as eligible for special education. Each decision is founded upon a judgment regarding whether the student has responded to intervention. These and other conclusions are inherently causal, thus requiring that educators carefully consider the internal, construct, and conclusion validity of each decision to ensure its defensibility. Researchers have identified multiple variables that are likely to moderate these validities, including the integrity with which interventions are implemented, the psychometric adequacy of progress-monitoring tools, the extent to which interventions and supports are matched to a student's needs, and the approach to single-case research design. We therefore review each of these variables in the interest of assisting practitioners to design acceptable and valid multitiered frameworks of prevention and service delivery. Keywords Response to intervention . Research methods . ValiditySchool-based multitiered frameworks, including response to intervention (RTI), have gained prominence as general service delivery models, emphasizing risk minimization through prevention, and early identification and intervention (Vaughn and Fuchs 2003). Recently, Kratochwill et al. (2012) reviewed the role of science within school psychological practice, illustrating the relationships between the RTI, scientist-practitioner, and evidence-based practice movements. The authors specified two main roles filled by school psychology scientistpractitioners. The first pertains to the consumption of scientific evidence. RTI is founded upon the use of evidence-based practices; schools are required to use interventions supported by scientific evidence, which serves as a preliminary indicator that such strategies are appropriate and likely to promote student outcomes. Judgment as to whether evidence is both scientific and sufficient to support applied use is a primary function of the scientist-practitioner . The second role is the generation of scientific evidence. Training in research methods and data analysis permits the scientist-practitioner to engage in practice-based research for the purpose of collecting evidence of the effectiveness of interventions and supports (Sidman 2011). Such research calls for the use of sophisticated methods and analyses, which together support the validity of inferences regarding intervention effectiveness and increase the likelihood of the evidence's contribution to the peer-reviewed literature. Many have called for the proliferation of such research, as it stands to both enhance the dissemination of evidence-based practices and determine how practices may be adapted to fit local contexts and enhance effectiveness .Although a focus on school psychologists as generators of evidence is necessary and crucial, we see potential for expansion to the definition of the scientist...

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The Impact of Baseline Trend Control on Visual Analysis of Single-Case Data

Cited by 25 publications

References 23 publications

Interrater Agreement Between Visual Analysts of Single-Case Data

Interrater Agreement Between Visual Analysts of Single-Case Data

Decision-Making Accuracy of CBM Progress-Monitoring Data

Applied Empiricism: Ensuring the Validity of Causal Response to Intervention Decisions

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