Single case and Small n Experimental Designs

Author: Pat Dugard
Publisher: Taylor & Francis
ISBN: 1136588477
Format: PDF, ePub
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This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies. The macros and example data are provided on the book’s website so that users can run analyses of the text data as well as data from their own studies. The new edition features: More explanation as to why randomization tests are useful and how to apply them. More varied and expanded examples that demonstrate the use of these tests in education, clinical work and psychology. A website with the macros and datasets for all of the text examples in IBM SPSS and Excel. Exercises at the end of most chapters that help readers test their understanding of the material. A new glossary that defines the key words that appear in italics when they are first introduced. A new appendix that reviews the basic skills needed to do randomization tests. New appendices that provide annotated SPSS and Excel macros to help readers write their own or tinker with the ones provided in the book. The book opens with an overview of single case and small n designs -- why they are needed and how they differ from descriptive case studies. Chapter 2 focuses on the basic concepts of randoization tests. Next how to choose and implement a randomization design is reviewed including material on how to perform the randomizations, how to select the number of observations, and how to record the data. Chapter 5 focuses on how to analyze the data including how to use the macros and understand the results. Chapter 6 shows how randomization tests fit into the body of statistical inference. Chapter 7 discusses size and power. The book concludes with a demonstration of how to edit or modify the macros or use parts of them to write your own. Ideal as a text for courses on single-case, small n design, and/or randomization tests taught at the graduate level in psychology (especially clinical, counseling, educational, and school), education, human development, nursing, and other social and health sciences, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this book’s accessible approach. An introduction to basic statistics, SPSS, and Excel is assumed.

Analysis of Clinical Trials Using SAS

Author: Alex Dmitrienko
Publisher: SAS Institute
ISBN: 1635261449
Format: PDF, Mobi
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Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition bridges the gap between modern statistical methodology and real-world clinical trial applications. Tutorial material and step-by-step instructions illustrated with examples from actual trials serve to define relevant statistical approaches, describe their clinical trial applications, and implement the approaches rapidly and efficiently using the power of SAS. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials. Commonly used methods are covered, including dose-escalation and dose-finding methods that are applied in Phase I and Phase II clinical trials, as well as important trial designs and analysis strategies that are employed in Phase II and Phase III clinical trials, such as multiplicity adjustment, data monitoring, and methods for handling incomplete data. This book also features recommendations from clinical trial experts and a discussion of relevant regulatory guidelines. This new edition includes more examples and case studies, new approaches for addressing statistical problems, and the following new technological updates: SAS procedures used in group sequential trials (PROC SEQDESIGN and PROC SEQTEST) SAS procedures used in repeated measures analysis (PROC GLIMMIX and PROC GEE) macros for implementing a broad range of randomization-based methods in clinical trials, performing complex multiplicity adjustments, and investigating the design and analysis of early phase trials (Phase I dose-escalation trials and Phase II dose-finding trials) Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience and the ready-to-use SAS macros compiled in this book.

Experimental Design and Statistics for Psychology

Author: Fabio Sani
Publisher: John Wiley & Sons
ISBN: 1405150386
Format: PDF, ePub, Docs
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Experimental Design and Statistics for Psychology: A First Course is a concise, straighforward and accessible introduction to the design of psychology experiments and the statistical tests used to make sense of their results. Makes abundant use of charts, diagrams and figures. Assumes no prior knowledge of statistics. Invaluable to all psychology students needing a firm grasp of the basics, but tackling of some of the topic’s more complex, controversial issues will also fire the imagination of more ambitious students. Covers different aspects of experimental design, including dependent versus independent variables, levels of treatment, experimental control, random versus systematic errors, and within versus between subjects design. Provides detailed instructions on how to perform statistical tests with SPSS. Downloadable instructor resources to supplement and support your lectures can be found at www.blackwellpublishing.com/sani and include sample chapters, test questions, SPSS data sets, and figures and tables from the book.

Research and Statistical Methods in Communication Sciences and Disorders

Author: David L. Maxwell
Publisher: Singular Publishing Group
ISBN: 9781401815677
Format: PDF, Docs
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This engaging new book provides comprehensive coverage of research methods as well as a foundation in statistical analysis vital for individuals in the communication sciences and disorders field. While most speech-language pathologists and audiologists pursue clinical practice rather than research careers, it is important to understand the scientific base that their clinical work is built upon. Successful evidence-based clinical practice is rooted in this understanding. Research and Statistical Methods in Communication Sciences and Disorders covers the principles of research design, data analysis, and presentation of findings necessary for individuals performing research as well as consumers of scientific literature. Filled with meaningful examples, written in readable language, and pertinent to both speech-language pathology and audiology, this resource provides the essential knowledge of scientific reasoning and methods for scientific inquiry necessary to perform and understand research.

Evaluating Practice

Author: Martin Bloom
Publisher: Allyn & Bacon
ISBN: 9780205466986
Format: PDF, ePub, Mobi
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"Focusing on single-system designs, Evaluating Practice, 6/e presents clear guidelines on conceptualizing and measuring problems, developing practice-oriented evaluation designs, understanding and analyzing data, and ethical guidelines for practice evaluation. Unsurpassed among human service evaluation texts for bringing clarity to evaluation procedures, Evaluating Practice comes with a free CD-ROM featuring numerous programs, including the innovative SINGWIN program for analyzing data (created by Charles Auerbach, David Schnall, and Heidi Heft Laporte of Yeshiva University), and the CASS and CAAP programs (created by Walter Hudson) for managing cases and scoring scales."--Publisher's Website.

The Good Research Guide

Author: Martyn Denscombe
Publisher: McGraw-Hill International
ISBN: 0335220223
Format: PDF, Mobi
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As a best-selling introductory book on the basics of social research, The Good Research Guide provides an accessible yet comprehensive introduction to the main approaches to social research and the methods most commonly used by researchers in the social sciences. This edition has been updated to account for recent developments in the field such as: The emergence of mixed methods approaches Increased use of internet research More frequent use of methods such as triangulation and focus groups Developments in research ethics Written for anyone undertaking a small-scale research project, either as part of an academic course or as part of their professional development, this book provides: A clear, straightforward introduction to data collection methods and data analysis Explanations of the key decisions researchers need to take, with practical advice on how to make appropriate decisions Essential checklists to guide good practice This book is perfect for the first-time researcher looking for guidance on the issues they should consider and traps they should avoid when embarking on a social research project.

Small Clinical Trials

Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 9780309171144
Format: PDF, ePub, Docs
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Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.

Designing Experiments and Analyzing Data

Author: Scott E. Maxwell
Publisher: Routledge
ISBN: 1317284550
Format: PDF, Docs
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Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features?further facilitate understanding:?examples of published research demonstrate the applicability of each chapter’s content; flowcharts?assist in choosing the most appropriate procedure;?end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and?extensive sets of exercises?help develop a deeper understanding of the subject.?Detailed solutions?for some of the exercises and?realistic data sets?are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

Multivariable Analysis

Author: Mitchell H. Katz
Publisher: Cambridge University Press
ISBN: 1139500317
Format: PDF, Docs
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Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression. As before, it focuses on easy-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.