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Beyond Significance Testing: Statistics Reform in the Behavioral Sciences, Second Edition Second Edition, Kindle Edition

by Rex B. Kline (Author) Format: Kindle Edition
4.5 4.5 out of 5 stars 4 ratings
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This accessibly written book reviews the controversy about significance testing, which has now crossed various disciplines as diverse as psychology, ecology, commerce, education, and biology, among others. It also introduces readers to alternative methods, especially effect size estimation (at both the group and case levels) and interval estimation (confidence intervals) in comparative studies. Basics of bootstrapping and Bayesian estimation are also considered. Research examples from substance abuse, education, learning, and other areas illustrate how to apply these methods.
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  1. ISBN-13
    978-1433812781
  2. Edition
    Second Edition
  3. Sticky notes
    On Kindle Scribe
  4. Publisher
    American Psychological Association
  5. Publication date
    March 31, 2013
  6. Language
    English
  7. File size
    22817 KB
  8. See all details
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Editorial Reviews

About the Author

Rex B. Kline, PhD, is a professor of psychology at Concordia University in Montréal, Canada. He has a doctorate in clinical psychology. His areas of research and writing include the psychometric evaluation of cognitive abilities, cognitive and scholastic assessment of children, structural equation modeling, the training of behavioral science researchers, and usability engineering in computer science. He has published six books and nine chapters in these areas.
 

Product details

  • ASIN ‏ : ‎ B00OY844NI
  • Publisher ‏ : ‎ American Psychological Association; Second Edition (March 31, 2013)
  • Publication date ‏ : ‎ March 31, 2013
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 22817 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Sticky notes ‏ : ‎ On Kindle Scribe
  • Print length ‏ : ‎ 328 pages
  • Customer Reviews:
    4.5 4.5 out of 5 stars 4 ratings

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Rex B. Kline

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Customer reviews

4.5 out of 5 stars
4.5 out of 5
4 global ratings

Top reviews from the United States

Freddy A. Paniagua
5.0 out of 5 stars Do you really need the null hypothesis?
Reviewed in the United States on June 25, 2017
Verified Purchase
This book will teach you why you should avoid an emphasis on the rejection of null hypothesis if you want to make
significant scientific contributions. Why do you need to formulate a null hypothesis if you know statistical tricks to reject it?
This is the central point in an article I am now writing for a peer-reviewed journal, and Dr. Kline's book is a very helpful text in my goal
to show that the null hypothesis can, indeed, prevents scientific advances and particularly when null results are important but rejected
by the peer-review process that only agrees with papers rejecting the null hypothesis. If you conduct an experiment and your "experimental hypothesis" claims that the Method A will be a good method to teach English to immigrant children from Latin America Countries, your null hypothesis claims the opposite of your expected results (i.e., Method A is not a good method to teach English ). If your results do not support your experimental hypothesis, you would have trouble finding a peer-reviewed journal to publish your null results. However, your results are still very important for the school district in your community because they inform that this district does not need to spend lots of money producing a method for teaching English that does not actually work or is not effective in achieving the goal of this district, namely, teaching English to immigrant children from Latin American countries. In this example, the administration of that school district will be very happy to know that your results did not reject the null hypothesis!
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eames
5.0 out of 5 stars Much needed corrective
Reviewed in the United States on May 18, 2013
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Problems with significance testing have been noted for years, yet elementary college textbooks and many, many social science publications rely heavily on it. Dr. Kline's offers an excellent overview of the problems with NHST and how other measures can offer more accurate insight into data.
6 people found this helpful
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Don
2.0 out of 5 stars Could have been an important contribution if it were only written better
Reviewed in the United States on January 3, 2014
Beyond Significance Testing raises important points about how data are often misinterpreted and how valuable resources are squandered in laboratory research and clinical trials because of inappropriate use of statistical analyses. This is an urgent issue with wide application and interest. Because BST is a work of worthwhile and original ideas, I am perplexed and disappointed by the author’s decision to cloak those ideas in turgid, textbook-like exposition. It really is a slog to get through this book.

The very idea that there are issues in statistics will be startling to many, and could be a powerful hook to draw in the potentially large audience of readers who use statistics in their profession. BST seems to be addressed to the author’s statistician colleagues rather than to researchers, clinicians, practitioners, policy-makers and students in many fields who could profit greatly from understanding the issues BST raises. This book, as it stands, is more likely to be a turn-off than a turn-on and that’s a shame.

Clearly, the field of statistics and its methods of analysis need to change. I hope for the next edition of this book the author will give some thought to how to increase the impact of his important and provocative ideas by presenting them in a way that can be more easily absorbed by those who can benefit most from his wisdom. In his own arresting formulation, "If psychologists are so smart, why are they so confused? Why is statistics carried out like compulsive handwashing?" (p. 95). Could it be that they, along with researchers in many other fields, need a supple, compelling, accessible, lucid, user-friendly account of statistics that can help them to think critically about, understand the meaning behind, and apply, statistical methods? It has been my experience and general impression (in over 45 years of doing biomedical research) that most statisticians are more interested in demonstrating their sagacity than in taking the time to teach effectively and well. This is as true of their writing as it is of their publications. Someone clearly needs to do better.
9 people found this helpful
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Top reviews from other countries

HK Soubhi
5.0 out of 5 stars This book is a wonderful mine of information and resources for all people who ...
Reviewed in Canada on December 25, 2016
Verified Purchase
This book is a wonderful mine of information and resources for all people who are serious about their science and what they can do with it when they choose to go beyond statistical significance testing. I simply love it +++
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