scholarly journals Assessing Intervention Effects in the Presence of Missing Scores

2021 ◽  
Vol 11 (2) ◽  
pp. 76
Author(s):  
Chao-Ying Joanne Peng ◽  
Li-Ting Chen
Keyword(s):  
Intervention Studies ◽  
Visual Analysis ◽  
Single Case ◽  
Internal Validity ◽  
Multiple Baseline ◽  
Single Case Design ◽  
Intervention Effect ◽  
Intervention Effects ◽  
Case Design ◽  
Support Evidence

Due to repeated observations of an outcome behavior in N-of-1 or single-case design (SCD) intervention studies, the occurrence of missing scores is inevitable in such studies. Approximately 21% of SCD articles published in five reputable journals between 2015 and 2019 exhibited evidence of missing scores. Missing rates varied by designs, with the highest rate (24%) found in multiple baseline/probe designs. Missing scores cause difficulties in data analysis. And inappropriate treatments of missing scores lead to consequences that threaten internal validity and weaken generalizability of intervention effects reported in SCD research. In this paper, we comprehensively review nine methods for treating missing SCD data: the available data method, six single imputations, and two model-based methods. The strengths, weaknesses, assumptions, and examples of these methods are summarized. The available data method and three single imputation methods are further demonstrated in assessing an intervention effect at the class and students’ levels. Assessment results are interpreted in terms of effect sizes, statistical significances, and visual analysis of data. Differences in results among the four methods are noted and discussed. The extensive review of problems caused by missing scores and possible treatments should empower researchers and practitioners to account for missing scores effectively and to support evidence-based interventions vigorously. The paper concludes with a discussion of contingencies for implementing the nine methods and practical strategies for managing missing scores in single-case intervention studies.

scholarly journals Commercial head-mounted display virtual reality for upper extremity rehabilitation in chronic stroke: a single-case design study

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Mattias Erhardsson ◽  
Margit Alt Murphy ◽  
Katharina S. Sunnerhagen
Keyword(s):  
Virtual Reality ◽  
Upper Extremity ◽  
Visual Analysis ◽  
Single Case ◽  
Chronic Stroke ◽  
Single Case Design ◽  
Head Mounted Display ◽  
U Statistics ◽  
Upper Extremity Rehabilitation ◽  
Case Design

Abstract Background Rehabilitation is crucial for maximizing recovery after stroke. Rehabilitation activities that are fun and rewarding by themselves can be more effective than those who are not. Gamification with virtual reality (VR) exploits this principle. This single-case design study probes the potential for using commercial off-the-shelf, room-scale head-mounted virtual reality for upper extremity rehabilitation in individuals with chronic stroke, the insights of which can inform further research. Methods A heterogeneous volunteer sample of seven participants living with stroke were recruited through advertisement. A single-case design was employed with a 5-week baseline (A), followed by a 10-week intervention (B) and a 6-month follow-up. Upper extremity motor function was assessed with validated kinematic analysis of drinking task. Activity capacity was assessed with Action Research Arm Test, Box and Block Test and ABILHAND questionnaire. Assessments were done weekly and at follow-up. Playing games on a VR-system with head-mounted display (HTC Vive) was used as rehabilitation intervention. Approximately 300 games were screened and 6 tested. Visual analysis and Tau-U statistics were used to interpret the results. Results Visual analysis of trend, level shift and overlap as well as Tau-U statistics indicated improvement of Action Research Arm Test in six participants. Four of these had at least a moderate Tau-U score (0.50–0.92), in at least half of the assessed outcomes. These four participants trained a total of 361 to 935 min. Two out of four participants who were able to perform the drinking task, had the highest training dose (> 900 min) and showed also improvements in kinematics. The predominant game played was Beat Saber. No serious adverse effects related to the study were observed, one participant interrupted the intervention phase due to a fall at home. Conclusions This first study of combining commercial games, a commercial head-mounted VR, and commercial haptic hand controls, showed promising results for upper extremity rehabilitation in individuals with chronic stroke. By being affordable yet having high production values, as well as being an easily accessible off-the-shelf product, this variant of VR technology might facilitate widespread adaption. Insights garnered in this study can facilitate the execution of future studies. Trial registration The study was registered at researchweb.org (project number 262331, registered 2019-01-30, https://www.researchweb.org/is/vgr/project/262331) prior to participant enrolment.

Evaluating Tau-U With Oral Reading Fluency Data and the Impact of Measurement Error

2018 ◽  
Vol 43 (3) ◽  
pp. 413-438 ◽  
Author(s):  
David A. Klingbeil ◽  
Ethan R. Van Norman ◽  
Katherine E. McLendon ◽  
Sarah G. Ross ◽  
John C. Begeny
Keyword(s):  
Reading Fluency ◽  
Oral Reading ◽  
Single Case ◽  
Effect Sizes ◽  
Multiple Baseline ◽  
Large Set ◽  
Single Case Design ◽  
Evidence Based Practices ◽  
The Impact ◽  
Case Design

Recently, researchers have argued that using quantitative effect sizes in single-case design (SCD) research may facilitate the identification evidence-based practices. Indices to quantify nonoverlap are among the most common methods for quantifying treatment effects in SCD research. Tau-U represents a family of effect size indices that were developed to address criticisms of previously developed measures of nonoverlap. However, more research is necessary to determine the extent to which Tau-U successfully addresses proposed limitations of other nonoverlap methods. This study evaluated Tau-U effect sizes, derived from multiple-baseline designs, where researchers used curriculum-based measures of reading (CBM-R) to measure reading fluency. Specifically, we evaluated the distribution of the summary Tau-U statistic when applied to a large set of CBM-R data and assessed how the variability inherent in CBM-R data may influence the obtained Tau-U values. Findings suggest that the summary Tau-U statistic may be susceptible to ceiling effects. Moreover, the results provide initial evidence that error inherent in CBM-R scores may have a small but meaningful influence on the obtained effect sizes. Implications and recommendations for research and practice are discussed.

An Examination of Fluoxetine for the Treatment of Selective Mutism Using a Nonconcurrent Multiple-Baseline Single-Case Design Across 5 Cases

2018 ◽  
Vol 24 (1) ◽  
pp. 2-14 ◽  
Author(s):  
JUSTIN A. BARTERIAN ◽  
JOEL M. SANCHEZ ◽  
JED MAGEN ◽  
ALLISON K. SIROKY ◽  
BRITTANY L. MASH ◽  
...  
Keyword(s):  
Single Case ◽  
Selective Mutism ◽  
Multiple Baseline ◽  
Single Case Design ◽  
Case Design

scholarly journals Systematic Use of Visual Analysis for Assessing Outcomes in Single Case Design Studies

2017 ◽  
Vol 19 (1) ◽  
pp. 4-17 ◽  
Author(s):  
Jennifer R. Ledford ◽  
Justin D. Lane ◽  
Katherine E. Severini
Keyword(s):  
Visual Analysis ◽  
Single Case ◽  
Summative Evaluation ◽  
Single Case Design ◽  
Design Studies ◽  
Dichotomous Responses ◽  
Single Case Designs ◽  
Evaluation Of Data ◽  
The Impact ◽  
Case Design

Single case designs (SCDs) allow researchers to objectively evaluate the impact of an intervention by repeatedly measuring a dependent variable across baseline and intervention conditions. Rooted in baseline logic, SCDs evaluate change over time, with each participant serving as his or her own control during the course of a study. Formative and summative evaluation of data is critical to determining causal relations. Visual analysis involves evaluation of level, trend, variability, consistency, overlap, and immediacy of effects within (baseline and intervention) and between conditions (baseline to intervention). The purpose of this paper is to highlight the process for visually analysing data collected in the context of a SCD and to provide structures and procedures for evaluating the six data characteristics of interest. A checklist with dichotomous responses (i.e., yes/no) is presented to facilitate implementation and reporting of systematic visual analysis.

The Effect of Different Types of Feedback Statements on Educators’ Use of Naturalistic Instruction

2021 ◽  
pp. 016264342110193
Author(s):  
Christan Grygas Coogle ◽  
Clarissa Bunch Wade ◽  
Jennifer R. Ottley ◽  
Laura McCorkle
Keyword(s):  
Professional Development ◽  
Early Childhood ◽  
Visual Analysis ◽  
Special Educators ◽  
Single Case ◽  
Single Case Design ◽  
Preschool Classrooms ◽  
Different Types ◽  
Case Design

We used an adapted alternating treatment single-case design to compare the effect of affirmative feedback to affirmative plus suggestive feedback on educators’ use of naturalistic instruction. Three early childhood special educators and a focus child within their preschool classrooms participated. Visual analysis of our data suggest that affirmative plus suggestive feedback produced stronger effects compared to affirmative feedback. Based on these data, faculty and professional development providers should plan to provide their educators with both affirmative and suggestive feedback to strengthen educators’ practice. Implications for practice and research are included.

Teaching academic skills to students with significant intellectual disabilities: A systematic review of the single-case design literature

2019 ◽  
pp. 174462951989538 ◽  
Author(s):  
Helen I Cannella-Malone ◽  
Scott A Dueker ◽  
Mary A Barczak ◽  
Matthew E Brock
Keyword(s):  
Systematic Review ◽  
Visual Analysis ◽  
Single Case ◽  
Academic Skills ◽  
Evidence Based ◽  
Single Case Design ◽  
Significant Disabilities ◽  
Evidence Based Practices ◽  
Basic Reading Skills ◽  
Case Design

Students with significant intellectual and developmental disabilities deserve access to instruction on academic skills in addition to functional skills. Many teachers, however, report challenges with identifying appropriate evidence-based practices to teach academics to these students. The purpose of this systematic review was to summarize and analyze literature on academic instruction for students with significant disabilities. Two hundred twenty-two articles with 225 experiments utilizing a single-case design and published between 1976 and 2018 were included in the review. Visual analysis indicated that, in most cases, interventions enabled students to make progress on targeted academic skills. The majority of studies focused on basic reading skills and included participants with moderate disabilities. Most studies used a combination of three or four evidence-based practices, with modeling, prompting, visual supports, time delay, and reinforcement being the most frequently used combination across studies.

An Investigation of SRSD to Teach Fractions to Students With Disabilities

2018 ◽  
Vol 85 (3) ◽  
pp. 291-308 ◽  
Author(s):  
Mickey Losinski ◽  
Robin Parks Ennis ◽  
Sara Sanders ◽  
Nicole Wiseman
Keyword(s):  
Students With Disabilities ◽  
Single Case ◽  
Treatment Fidelity ◽  
Multiple Baseline ◽  
Strategy Development ◽  
Future Research ◽  
Single Case Design ◽  
Intervention Package ◽  
Research Questions ◽  
Case Design

In the current study we examined the effect of a self-regulated strategy development intervention on the fraction calculations of students with or at risk for disabilities using a multiple-baseline-across-sites, single-case design. Specifically, the intervention package addressed the following skills: adding and subtracting fractions with unlike denominators, simplifying fractions, and converting improper fractions to mixed numbers. The intervention was implemented with high levels of treatment fidelity and social validity across three separate intervention agents. Results of the study showed the intervention to be effective, with 15 of the 16 participants making marked gains on fraction probes. We discuss the results of the study with respect to the research questions, provide limitations to the study, and propose areas for future research.

Single-Case Design

2017 ◽  
Author(s):  
Shirin D. Antia ◽  
Caroline Guardino ◽  
Joanna E. Cannon
Keyword(s):  
Instructional Strategies ◽  
Single Case ◽  
Deaf Education ◽  
Evidence Base ◽  
Multiple Baseline ◽  
Single Case Design ◽  
Validity And Reliability ◽  
Multiple Treatment ◽  
Research Designs ◽  
Case Design

Key features of single-case design (SCD) research are presented and reviewed, including AB, withdrawal (ABAB), multiple-baseline, multiple-treatment, and comparative designs. Validity and reliability of these research designs are defined. The relevance and feasibility of using SCD research to build an evidence base of instructional strategies is discussed. Studies within the field of deaf education are examined and analyzed to demonstrate the variety of ways that SCD research can be implemented in the field. Recommendations regarding replication, collaboration, and generalization are noted to encourage researchers to implement SCD studies to advance the field.

Graphing Data and Visual Analysis

2019 ◽  
pp. 71-88
Author(s):  
Keith C. Radley ◽  
Evan H. Dart
Keyword(s):  
Quality Indicators ◽  
Student Behavior ◽  
Visual Analysis ◽  
Single Case ◽  
Evidence Based ◽  
Single Case Design ◽  
Evidence Based Practices ◽  
Data Points ◽  
Evaluation Of Evidence ◽  
Case Design

As previously described, single-case design has several advantages in the evaluation of evidence-based practices and for the evaluation of the effects of interventions in applied settings. Following collection of data, data are typically graphed in order to determine the effects of an intervention on student behavior. However, recent research has determined that the manner in which graphs are constructed is likely to impact the decisions that visual analysts make regarding the effect of an intervention. As such, it is important that graphs be constructed in a manner that minimizes potential for error. This chapter describes quality indicators for graphs, and discusses analysis- and aesthetic-altering elements of graphs. In particular, the chapter describes two analysis-altering elements that must be considered when constructing graphs: scaling of the y-axis and the data points per x- to y-ratio (DPPXYR). Finally, the chapter describes how to conduct visual analysis. Six elements are discussed: changes in level, trend, and variability, consistency across similar conditions, overlap across adjacent phases, and immediacy of intervention effects.

scholarly journals Proportional Reasoning Interventions in Special Education Synthesis Coding Protocol

2021 ◽  
Author(s):  
Gena Nelson
Keyword(s):  
Interrater Reliability ◽  
Intervention Studies ◽  
Single Case ◽  
Proportional Reasoning ◽  
Single Case Design ◽  
Instructional Content ◽  
Study Results ◽  
The Mean ◽  
Code Book ◽  
Case Design

The purpose of document is to provide readers with the coding protocol that authors used to code nine group and single case design intervention studies focused on proportional reasoning interventions for students (grades 5-9) with learning disabilities (LD) or mathematics difficulty (MD). The studies yielded intervention effects ranging from g = −0.10 to 1.87 and from Tau-U = 0.88 to 1.00. We coded all of the studies for variables in the following categories: study information, intervention features, dependent measures, participant demographics, LD and MD criteria and definitions, instructional content, study results, and quality indicators for group and single case design. The study quality indicator coding portion of this coding protocol was adapted from Gersten et al. (2005) and Horner et al. (2005). This code book contains variable names, code options, and code definitions. The mean interrater reliability across all codes using this protocol was 91% (range across categories = 82%–96%). The publication associated with this coding protocol is Nelson et al. (2020).

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