E-Book, Englisch, 472 Seiten
E-Book, Englisch, 472 Seiten
Reihe: Multivariate Applications Series
ISBN: 978-1-317-84361-0
Verlag: CRC Press
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
The book is organized into five general areas. The first presents an overview of significance testing issues that sythesizes the highlights of the remainder of the book. The next discusses the debate in which significance testing should be rejected or retained. The third outlines various methods that may supplement current significance testing procedures. The fourth discusses Bayesian approaches and methods and the use of confidence intervals versus significance tests. The last presents the philosophy of science perspectives.
Rather than providing definitive prescriptions, the chapters are largely suggestive of general issues, concerns, and application guidelines. The editors allow readers to choose the best way to conduct hypothesis testing in their respective fields. For anyone doing research in the social sciences, this book is bound to become "must" reading.
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Contents: Preface. Part I: Overview. L.L. Harlow, Significance Testing Introduction and Overview. Part II: The Debate: Against and For Significance Testing. J.Cohen, The Earth Is Round. F.L. Schmidt, J. Hunter, Eight Objections to the Discontinuation of Significance Testing in the Analysis of Research Data. S.A. Mulaik, N.S. Raju, R. Harshman, There Is a Time and Place for Significance Testing. R.P. Abelson, A Retrospective on the Significance Test Ban of 1999 (If There Were No Significance Tests, They Would Be Invented). Part III: Suggested Alternatives to Significance Testing. R.J. Harris, Reforming Significance Testing via Three-Valued Logic. J.S. Rossi, Spontaneous Recovery of Verbal Learning: A Case Study in the Failure of Psychology as a Cumulative Science. J.H. Steiger, R.T. Fouladi, Noncentrality Interval Estimation and the Evaluation of Statistical Models. R.P. McDonald, Goodness of Approximation in the Linear Model. Part IV: A Bayesian Approach to Hypothesis Testing. R.M. Pruzek, An Introduction to Bayesian Inference and Its Application. D. Rindskopf, Testing 'Small,' Not Null, Hypotheses: Classical and Bayesian Approaches. C.S. Reichardt, H.F. Gollob, When Confidence Intervals Should Be Used Instead of Statistical Significance Tests, and Vice Versa. Part V: Philosophy of Science Issues. W.W. Rozeboom, Good Science Is Abductive, Not Hypothetico-Deductive. P.E. Meehl, The Problem Is Epistemology, Not Statistics: Replace Significance Tests by Confidence Intervals and Quantify Accuracy of Risky Numerical Predictions.