Ssd for R An R Package For Analyzing Single-Subject Data

211 Pages·2014·6.04 MB·English

by  Charles Auerbach

SSD FOR R: AN R PACKAGE FOR
ANALYZING SINGLE-SUBJECT DATA
SSD FOR R: AN R PACKAGE FOR
ANALYZING SINGLE-SUBJECT
DATA
Charles Auerbach, PhD.
and
Wendy Zeitlin, PhD.
Oxford University Press is a department of the University of Oxford. It furthers the University’s objective
of excellence in research, scholarship, and education by publishing worldwide.
Oxford New York
Auckland Cape Town Dar es Salaam Hong Kong Karachi Kuala Lumpur Madrid Melbourne Mexico City
Nairobi New Delhi Shanghai Taipei Toronto With offices in
Argentina Austria Brazil Chile Czech Republic France Greece Guatemala Hungary Italy Japan Poland
Portugal Singapore South Korea Switzerland Thailand Turkey Ukraine Vietnam Oxford is a registered
trademark of Oxford University Press in the UK and certain other countries.
Published in the United States of America by Oxford University Press
198 Madison Avenue, New York, NY 10016
© Oxford University Press 2014
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or
transmitted, in any form or by any means, without the prior permission in writing of Oxford University
Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction
rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the
Rights Department, Oxford University Press, at the address above.
You must not circulate this work in any other form and you must impose this same condition on any
acquirer.
Library of Congress Cataloging-in-Publication Data Auerbach, Charles.
SSD for R : an R package for analyzing single-subject data / by Charles Auerbach, PhD. &
Wendy Zeitlin, PhD.
pages cm
ISBN 978–0–19–934359–1 (paperback) eISBN 978–0–19–934361–4
1. Social sciences—Research. 2. Single subject research. I. Zeitlin, Wendy. II. Title.
H62.A8493 2014
001.4′2—dc23
2014000957
To my dear friend and mentor, George Rothbart
To the memory of my grandfather, Harold Landau, who first taught me about
probability
And to the memory of Aaron Beckerman
CONTENTS
Introduction: Single-Subject Research Designs in the Social and Health
Sciences
1. Getting your Data into SSD for R
2. Overview of SSD for R Functions
3. Analyzing Baseline Phase Data
4. Comparing Baseline and Intervention Phases: Visualizing Your Findings and
Descriptive Statistics
5. Statistical Tests of Type I Error
6. Analyzing Group Data
7. Building Support for Practice Research
References
Appendix A Entering and Editing Data Directly in R
Appendix B SSD for R Quick Functions Guide
Appendix C Decision Trees
Appendix D Bibliography of Additional Resources
Index
INTRODUCTION
Single-Subject Research Designs in the Social and
Health Sciences
INTRODUCTION
This introduction will provide background information on single-subject
research and its use in the social and health sciences. Here you will find a brief
history of the use of this type of research design to provide a backdrop for its
current use and a discussion of future directions in the use of these. The purpose
of this is to provide contextual information for the introduction of SSD for R, a
visual and statistical software package that is easily accessible and useful in the
analysis of single-subject data. SSD for R is a package written in R, a free and
open-source statistical programming language (The R Project for Statistical
Computing, n.d.).
DESCRIPTION AND USAGE OF SINGLE-SUBJECT
RESEARCH
Single-subject research is also referred to in the literature as “n=1 research,”
“interrupted time series research,” and “single-case research.” Single-subject
research designs are substantively different from the more commonly published
group research designs; instead of examining aggregate data for multiple
research subjects simultaneously, single-subject research is concerned with the
empirical examination of a single research subject over time. While a single
research subject could mean an individual, it could be any subject that could be
conceptualized to be a single unit. For example, single-subject research could
just as easily use a couple, family, therapeutic group, community, or even a
larger population as its unit of analysis.
Single-subject research has some unique characteristics that differentiate it
from other types of research designs. First, the most common use of this is in the
evaluation of interventions (Smith, 2012). In single-subject research, however,
the subject serves as his or her own control. To accommodate this, single-subject
research designs typically collect data using frequent repeated measures over
time with collected data being assigned to phases (e.g., baseline, intervention)
with the baseline phase often being used as the control. Therefore, single-subject
research is a type of time series in which the series may be interrupted with the
introduction or withdrawal of one or more interventions.
Single-subject research, although quantitative, has some of the characteristics
of narrative case studies that focus on individuals. Like case studies, single-
subject research often contains a detailed description of the subject and, unlike
group designs, also contains a detailed description of the intervention or
experimental condition (Kazdin, 2011). However, with its inclusion of repeated
measures, single-subject research adds a level of methodological rigor often not
found in qualitative case studies. To this end, single-subject research falls into
the realm of scientific, quasi-experimental research, while narrative case studies
are considered pre-scientific (Miller, n.d.).
Unlike other research designs, single-subject research can have two distinct,
but equally important, purposes: for formal research such as studies published in
peer-reviewed journals and the less formal evaluation of practice. In terms of
formal research, single-subject studies have been published in a wide-variety of
social science, health, and allied health fields, including social work,
psychology, education, speech therapy, rehabilitation medicine, occupational
therapy, physical therapy, and physiology. The advantages of utilizing single-
subject research designs include the ability to examine problems that are rare or
to examine unique client/patient populations (Janosky, Leininger, Hoerger, &
Libkuman, 2009).
With regard to practice evaluation, single-subject research techniques can be
used empirically to evaluate client progress over time, simply and dynamically.
Techniques used to capture and evaluate client data in order to do this type of
analysis are easily learned, inexpensive, simple to implement, and can be built
into the normative relationship between clients and practitioners. The benefit to
including this type of evaluation into one’s practice is the ability to more
accurately evaluate client progress longitudinally, which can then be used to
inform the practitioner’s work with individual clients. That is, practitioners can
readily evaluate their clients’ progress over time to adapt their work to meet the
individual needs of those they serve.
THE HISTORY OF SINGLE-SUBJECT RESEARCH
Single-subject research has long been part of the repertoire of inquiry in the
social and health sciences. Some of the earliest known research using these
designs were the physiological studies conducted by Mueller and Bernard in the
1830s (Krishef, 1991). From the late 1880s through the early 1900s, a good deal
of experimental psychology focused on only one or a few subjects. These
included Pavlov’s quantitative analyses, Breuer’s qualitative cases studies, and
Ebbinghaus’s memory studies (Kazdin, 2011; Krishef, 1991).
In the early to mid-1900s, there was a general shift in research to studying
groups instead of individuals. This has been attributed to the development and
popularity of group statistical techniques, such as the t-test. Group analysis, then,
gained favor as it is difficult to attain statistical significance with small sample
sizes, including the typical number of small observations found in most single-
subject research designs. Therefore, experimental group designs became more
popular due to their scientific rigor (Kazdin, 2011; Krishef, 1991).
Learning and behavioral analysis, such as the type studied by Skinner, became
the forerunner of modern single-subject research designs (Kazdin, 2011). In
those studies, research was used to develop and refine theory (Smith, 2012).
Additionally, measures used were behaviorally based, often noting the frequency
of a target behavior. This allowed for the close examination of the impact of an
intervention on an individual that simply could not be detected using group
analysis. This research focused less on statistical analysis and more on systemic
change over time (Kazdin, 2011).
In the early 1970s, Bergin and Strupp noted the inherent limitations of group
research designs. These included the high costs associated with conducting
group research, the ethical issues related to assigning subjects to control
conditions, the difficulty of applying results from group analyses to individual
clients, and the difficulty in explaining why some subjects would improve with
treatment, while others did not (Krishef, 1991). More recently, questions have
continued to be posed about the utility of group findings from randomized
control trials to actual practice settings. This concern has resulted in a renewed
interest in the area of single-subject research designs (Smith, 2012).
SINGLE-SUBJECT RESEARCH TODAY
In recent years, the scientific community has again, embraced single-subject
research, but it is also growing in relevance due to professional organizations
that espouse high practice standards of its membership. For example, in 2008,
the Council on Social Work Education (CSWE), the accrediting body of schools
of social work in the United States, specifically identified two areas in which
single-subject research would be appropriate in its Educational Policy and
Accreditation Standards. Standard 2.1.6 states that accredited professional social
work programs need to teach students to “engage in research-informed practice
and practice informed research,” and Standard 2.1.10(d) directs programs to
teach “social workers [to] critically analyze, monitor, and evaluate
interventions.” (Council on Social Work Education (CSWE), 2008) Similarly,
the National Association of Social Workers’ (NASW) Code of Ethics requires
social workers to evaluate their own practices under Ethical Standard 5.02—
Evaluation and Research. Specifically, “social workers should monitor and
evaluate policies, the implementation of programs, and practice interventions,”
and “social workers should critically examine and keep current with emerging
knowledge relevant to social work and fully use evaluation and research
evidence in their professional practice.” (National Association of Social
Workers, 2008) While single-subject research is not the only way to evaluate
clinical practice, the techniques available in these designs are easy to learn and
congruent with the goals set forth by both CSWE and NASW.
Additionally, the evidence-based practice movement has attempted to bring
more rigor into practice settings by incorporating scientific research into clinical
work with the hope of improved service to clients (Thyer & Myers, 2011). To
this end, single-subject research designs have been used to build evidence to the
effective treatment of problems such as ADHD and other behavioral disorders,
schizophrenia, and depersonalization disorder (Nathan & Gorman, 2002;
Schudrich, 2012). One of the advantages to doing this type of research is the
ability to evaluate interventions as they are delivered in practice settings with
actual clients, which differs dramatically from group intervention designs
(Beddoe, 2011). In this way, practice-based research can be used to help bridge
the translational research gap between group research designs and actual
practice.
Single-subject research designs are considered for inclusion in systematic
reviews by respected groups such as the Cochrane and Campbell Collaborations,
provided they are scientifically rigorous (Higgins & Green, 2011; Schlosser &
Wendt, 2008; Scruggs & Mastropieri, 2013; Wendt, 2009). With systematic
replication of single-subject research, studies can uncover causal relationships
between an intervention and the dependent variable (Schlosser & Wendt, 2008).
In order to help elevate what constitutes scientifically rigorous single-subject
studies, various groups valuing this type of research have developed research
standards. These groups include The What Works Clearinghouse from the US
Department of Education, The National Institute of Child Health and Human
Development and several divisions of the American Psychological Association:
Division 12 (clinical psychology), Division 53 (clinical child and adolescent
psychology), and Division 16 (evidence-based practice in school psychology)
(Smith, 2012; Thyer & Myers, 2011). Common standards found across some of
these groups include: