SSD for R

2021 ◽  
Author(s):  
Charles Auerbach ◽  
Wendy Zeitlin
Keyword(s):  
Data Analysis ◽  
Visual Analysis ◽  
Statistical Significance ◽  
Single Subject ◽  
Single Subject Research ◽  
Level Data ◽  
Wide Range ◽  
Research Designs ◽  
Range Of Functions ◽  
Statistical Programming

Single-subject research designs have been used to build evidence to the effective treatment of problems across various disciplines, including social work, psychology, psychiatry, medicine, allied health fields, juvenile justice, and special education. This book serves as a guide for those desiring to conduct single-subject data analysis. The aim of this text is to introduce readers to the various functions available in SSD for R, a new, free, and innovative software package written in R, the robust open-source statistical programming language written by the book’s authors. SSD for R has the most comprehensive functionality specifically designed for the analysis of single-subject research data currently available. SSD for R has numerous graphing and charting functions to conduct robust visual analysis. Besides the ability to create simple line graphs, features are available to add mean, median, and standard deviation lines across phases to help better visualize change over time. Graphs can be annotated with text. SSD for R contains a wide variety of functions to conduct statistical analyses traditionally conducted with single-subject data. These include numerous descriptive statistics and effect size functions and tests of statistical significance, such as t tests, chi-squares, and the conservative dual criteria. Finally, SSD for R has the capability of analyzing group-level data. Readers are led step by step through the analytical process based on the characteristics of their data. Numerous examples and illustrations are provided to help readers understand the wide range of functions available in SSD for R and their application to data analysis and interpretation.

N = 1 Research Methodology in Counselling: Focusing upon the Individual Client

2003 ◽  
Vol 13 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Christopher F. Sharpley
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Single Subject ◽  
Health Practitioner ◽  
Design Data ◽  
Single Subject Research ◽  
Research Designs ◽  
Research Findings ◽  
Individual Client ◽  
The Individual

Although the last 20years have seen a focus upon evidence-based therapies, there are arguments that much of the so-called “evidence” produced is, in fact, irrelevant to the mental health practitioner in the field, principally because of the use of large-scale group designs in clinical controlled studies of the effectiveness of one therapy over another. By contrast, and with particular relevance to the practitioner who is both scientist and therapist, single subject research designs and methodologies for data analysis can be applied in ways that allow for generalisation to everyday practice. To inform the readership, the rationale underlying n = 1 studies is described, with some explanation of the major designs and their application to typical cases in guidance and counselling. Issues of inferential deductions from data, variations of design, data analysis via visual and statistical procedures, and replication are discussed. Finally, a case is argued for the introduction of n = 1 reports within the Australian Journal of Guidance and Counselling to better inform the readership about clinical research findings relevant to their practices.

Repeated Measures Designs

1999 ◽  
Vol 27 (4) ◽  
pp. 552-578 ◽  
Author(s):  
Michael V. Ellis
Keyword(s):  
Repeated Measures ◽  
Single Subject ◽  
Psychology Research ◽  
Applied Psychology ◽  
Single Subject Research ◽  
Repeated Measures Design ◽  
Wide Range ◽  
Research Designs ◽  
Repeated Measures Designs

To facilitate innovation in applied psychology research, investigators need to be well-informed about available research designs. The purpose of this article is to provide an overview of repeated measures research designs (e.g., participants exposed to more than one treatment or measured on more than one occasion). My intent is twofold. First, I underscore the wide range of repeated measures research designs available to researchers in applied psychology. Second, I argue that the differentiation and polarity of group and single-subject research designs is largely arbitrary. I use examples to illustrate each repeated measures design and present its strengths and limitations.

Comparative Effects of High-Tech Visual Scene Displays and Low-Tech Isolated Picture Symbols on Engagement From Students With Multiple Disabilities

2019 ◽  
Vol 50 (4) ◽  
pp. 693-702 ◽  
Author(s):  
Christine Holyfield ◽  
Sydney Brooks ◽  
Allison Schluterman
Keyword(s):  
Language Learning ◽  
Augmentative And Alternative Communication ◽  
Visual Analysis ◽  
Multiple Disabilities ◽  
Visual Scene ◽  
Future Research ◽  
High Tech ◽  
Single Subject ◽  
Wide Range ◽  
The Difference

Purpose Augmentative and alternative communication (AAC) is an intervention approach that can promote communication and language in children with multiple disabilities who are beginning communicators. While a wide range of AAC technologies are available, little is known about the comparative effects of specific technology options. Given that engagement can be low for beginning communicators with multiple disabilities, the current study provides initial information about the comparative effects of 2 AAC technology options—high-tech visual scene displays (VSDs) and low-tech isolated picture symbols—on engagement. Method Three elementary-age beginning communicators with multiple disabilities participated. The study used a single-subject, alternating treatment design with each technology serving as a condition. Participants interacted with their school speech-language pathologists using each of the 2 technologies across 5 sessions in a block randomized order. Results According to visual analysis and nonoverlap of all pairs calculations, all 3 participants demonstrated more engagement with the high-tech VSDs than the low-tech isolated picture symbols as measured by their seconds of gaze toward each technology option. Despite the difference in engagement observed, there was no clear difference across the 2 conditions in engagement toward the communication partner or use of the AAC. Conclusions Clinicians can consider measuring engagement when evaluating AAC technology options for children with multiple disabilities and should consider evaluating high-tech VSDs as 1 technology option for them. Future research must explore the extent to which differences in engagement to particular AAC technologies result in differences in communication and language learning over time as might be expected.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

Single-Subject Research Designs for Optometry

1985 ◽  
Vol 62 (8) ◽  
pp. 516-522 ◽  
Author(s):  
FRANK L. COLLINS ◽  
RUTH A. BAER ◽  
RONALD L. BLOUNT
Keyword(s):  
Single Subject ◽  
Single Subject Research ◽  
Research Designs

Single-subject research designs for group counselors studying their own groups

1989 ◽  
Vol 14 (2) ◽  
pp. 93-97 ◽  
Author(s):  
Floyd F. Robison ◽  
D. Keith Morran ◽  
Diana Hulse-killacky
Keyword(s):  
Single Subject ◽  
Single Subject Research ◽  
Research Designs ◽  
Group Counselors

Educational Validity Revisited

1987 ◽  
Vol 12 (2) ◽  
pp. 96-102 ◽  
Author(s):  
David W. Test ◽  
Fred Spooner ◽  
Nancy L. Cooke
Keyword(s):  
Research Methodology ◽  
Severe Disabilities ◽  
Educational Programs ◽  
Single Subject ◽  
Single Subject Research ◽  
Research Designs

In 1983, Voeltz and Evans introduced a set of criteria for establishing educational validity. Their intent was to improve the documentation of quality educational programs for learners with severe disabilities. Although the concept of educational validity is sound, we feel that Voeltz and Evans were not justified in rejecting single-subject research methodology as a vehicle for assessing educational validity. The present paper (a) provides a summary of the arguments of Voeltz and Evans against the use of single-subject research designs in establishing educational validity, (b) addresses each of the major concerns of Voeltz and Evans with single-subject research methodology, and (c) demonstrates how single-subject research methodology can be used to demonstrate educational validity.

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