Statistical Methods and Reasoning for the Clinical Sciences: Evidence-Based Practice

Plural Publishing
Free sample

Statistical Methods and Reasoning for the Clinical Sciences: Evidence-Based Practice provides practitioners with the scientific literacy needed to understand statistical methods in order to increase the accuracy of their diagnoses.

With case studies included on a companion website, this text will help readers comprehend how the process of clinical research relates to the scientific method of problem solving. Readers will understand the importance of three key, interrelated tasks involved in a research study: description (why it was done), explanation (what was done and to whom), and contextualization (how the results relate to other bodies of knowledge).

This text also examines the following:

The two basic elements of statistical reasoning that constitute evidence-based practice: deductive inference (from effect to cause) and inductive inference (from cause to effect).Classical statistical methods-statistical terms/vocabulary, population parameters, and sampling methods-as well as descriptive statistical methods-measures, correlation, and regression.The fundamentals of statistical inference that include testing hypotheses using a z-test, t-test, ANOVA, and MANOVA.The concept of probability, through various concrete examples and a step-by-step approach, which is a fundamental part of the clinical decision-making process.Evidence-based probabilistic methods called Minimum Bayes Factor (MBF) for measuring the strength of clinical evidence more precisely and as an alternative to classical testing hypotheses methods.Rationales and procedures of other statistical methods frequently seen in clinical literature, like meta-analysis, nonparametric methods, categorical analyses, and single subject designs.

This text not only distinguishes between the concepts of "statistical significance" and "clinical significance," often not clearly addressed in other texts, but it also emphasizes the value of scientific literacy in evidence-based practice. 

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About the author

Eiki Satake, PhD, is an associate professor of mathematics and statistics at Emerson College in Boston, Massachusetts. He has written numerous scholastic articles and instructional textbooks on statistical methods and statistics education. He has also conducted several research seminars and short courses on evidence-based statistics at national and international academic conferences. His research interests include Bayesian statistical methods and probabilistic approaches to evidence-based practice.

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Additional Information

Publisher
Plural Publishing
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Published on
Aug 1, 2014
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Pages
592
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ISBN
9781597566575
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Language
English
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Genres
Medical / Audiology & Speech Pathology
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Content Protection
This content is DRM protected.
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Read Aloud
Available on Android devices
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Eligible for Family Library

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Presented is a brief evaluation of the strengths and limitations of the test along with its suitability, or lack thereof, for particular scales of measurement. Also included are statistical applications of such computer programs as Minitab and SPSS for the analysis of statistical data. This new handbook provides the readers with a concise yet comprehensive approach to help them further understand the concepts as effectively and simply as possible. 

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* Diagrams, charts, illustrations, summary tables, a substantial glossary, a detailed index, and rich up-to-date references
* Systematic queries that enliven clear learning objectives


Pedagogy includes:

* Extensive assessment resources and a process analysis approach for analyzing communicative performance and interpreting assessment results
* Clear and concise clinical examples to ensure relevance of information based on realistic scenarios
* Systematic queries that enliven clear learning objectives
* Diagrams, charts, illustrations, summary tables, a substantial glossary, a detailed index, and rich up-to-date references
* Key terms in bold within the chapter and listed in a glossary

Disclaimer: Please note that ancillary content (such as documents, audio, and video, etc.) may not be included as published in the original print version of this book. 

Eiki Satake
In the behavioral and clinical sciences, single-subject designs have increasingly become important tools for determining a treatment efficacy. Despite a large number of recommendations in recent years for more use of the designs, the majority of typical research methods textbooks still do not provide sufficient direction and information about single-subject designs. One of the main reasons is that data analysis of single-subject designs is still foreign to the vast majority of the investigators, practitioners, and students. 

With this book, the authors have developed a practical guide of the most commonly used approaches in analyzing and interpreting single-subject data. In doing so, they have arranged the methodologies used in a logical sequence using an array of research studies from the existing published literatures to illustrate specific applications. The handbook is also laid out for the readers in a highly lucid and straightforward manner, beginning with a brief discussion of each approach such as visual, inferential, and probabilistic model, the applications for which it is intended, and a step-by-step illustration of the test as used in an actual research study. 

Presented is a brief evaluation of the strengths and limitations of the test along with its suitability, or lack thereof, for particular scales of measurement. Also included are statistical applications of such computer programs as Minitab and SPSS for the analysis of statistical data. This new handbook provides the readers with a concise yet comprehensive approach to help them further understand the concepts as effectively and simply as possible. 

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