Beyond Significance Testing

Beyond Significance Testing

Author: Rex B. Kline

Publisher: American Psychological Association (APA)

Published: 2015-05-09

Total Pages: 363

ISBN-13: 9781433812798

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Rev ed. of: Beyond significance testing: reforming data analysis methods in behavioral research. c2004.


Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research

Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research

Author: Rex B. Kline

Publisher: Amer Psychological Assn

Published: 2004-01-01

Total Pages: 325

ISBN-13: 9781591471189

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Annotation "The book is intended for applied researchers and students who may not have quantitative backgrounds. Readers will learn how to measure effect size on continuous or dichotomous outcomes in comparative studies with independent or dependent samples. They will also learn how to calculate and correctly interpret confidence intervals for effect sizes. Numerous research examples from a wide range of areas illustrate how to apply these principles and how to estimate substantive significance instead of just statistical significance. Additional alternatives to statistical tests are described, including meta-analysis, resampling techniques like bootstrapping, and Bayesian estimation."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved.


Beyond Significance Testing

Beyond Significance Testing

Author: Rex B. Kline

Publisher: Amer Psychological Assn

Published: 2013

Total Pages: 349

ISBN-13: 9781433812781

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Traditional education in statistics that emphasises significance testing leaves researchers and students ill prepared to understand what their results really mean. Specifically, most researchers and students who do not have strong quantitative backgrounds have difficulty understanding outcomes of statistical tests. As more and more people become aware of this problem, the emphasis on statistical significance in the reporting of results is declining. Increasingly, researchers are expected to describe the magnitudes and precisions of their findings and also their practical, theoretical, or clinical significance. 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. A companion website promotes learning by providing chapter exercises and sample answers, downloadable raw data files for many research examples, and links to other useful websites. New to this edition is coverage of robust statistical methods for parameter estimation, effect size estimation, and interval estimation. A new chapter covers the logic and illogic of significance testing. This edition also addresses recent developments such as the new requirements of some journals for the reporting of effect sizes.


Studyguide for Beyond Significance Testing

Studyguide for Beyond Significance Testing

Author: Cram101 Textbook Reviews

Publisher: Cram101

Published: 2013-08

Total Pages: 82

ISBN-13: 9781490245775

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Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9781433812781. This item is printed on demand.


Statistical Inference as Severe Testing

Statistical Inference as Severe Testing

Author: Deborah G. Mayo

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 503

ISBN-13: 1108563309

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Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.


Tests of Significance

Tests of Significance

Author: Ramon E. Henkel

Publisher: SAGE

Published: 1976-09

Total Pages: 100

ISBN-13: 9780803906525

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An elementary introduction to significance testing, this paper provides a conceptual and logical basis for understanding these tests.


Statistical Power Analysis for the Behavioral Sciences

Statistical Power Analysis for the Behavioral Sciences

Author: Jacob Cohen

Publisher: Routledge

Published: 2013-05-13

Total Pages: 625

ISBN-13: 1134742770

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Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.


Applied Social Science Approaches to Mixed Methods Research

Applied Social Science Approaches to Mixed Methods Research

Author: Baran, Mette Lise

Publisher: IGI Global

Published: 2019-10-25

Total Pages: 315

ISBN-13: 1799810275

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Research that has been presented primarily by quantitative research can benefit from the voice of the participants and the added value of the different perspective that qualitative research can provide. The purpose of mixed methods research is to draw from the positive aspects of both research paradigms to better answer the research question. This type of research is often used in schools, businesses, and non-profit organizations as they strive to address and resolve questions that will impact their organizations. Applied Social Science Approaches to Mixed Methods Research is an academic research publication that examines more traditional and common research methods and how they can be complimented through qualitative counterparts. The content within this publication covers an array of topics such as entrepreneurship, social media, and marginalization. It is essential for researchers, academicians, non-profit professionals, business professionals, and higher education faculty, and specifically targets master or doctoral students committed to writing their theses, dissertations, or scholarly articles, who may not have had the benefit of working on a traditional research team.


The Cult of Statistical Significance

The Cult of Statistical Significance

Author: Stephen Thomas Ziliak

Publisher: University of Michigan Press

Published: 2008-02-19

Total Pages: 349

ISBN-13: 0472050079

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How the most important statistical method used in many of the sciences doesn't pass the test for basic common sense


Communication Research Statistics

Communication Research Statistics

Author: John C. Reinard

Publisher: SAGE Publications

Published: 2006-04-20

Total Pages: 604

ISBN-13: 1506320481

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"While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected "calculators" for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences