What If There Were No Significance Tests? (eBook, PDF)

Classic Edition
Redaktion: Harlow, Lisa L.; Steiger, James H.; Mulaik, Stanley A.

• Format: PDF

Produktbeschreibung

The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 444
• Erscheinungstermin: 2. März 2016
• Englisch
• ISBN-13: 9781317242857
• Artikelnr.: 44867309

Autorenporträt

Lisa L. Harlow is Professor of Psychology at the University of Rhode Island. She is the Editor of Psychological Methods and a past president of the American Psychological Association's Division 5. Stanley A. Mulaik is Professor Emeritus of Psychology at Georgia Institute of Technology. His research interests include philosophy of statistics and causality and objectivity. James H. Steiger is Professor of Psychology and Human Development at Vanderbilt University. His research interests include the use of confidence intervals to evaluate the fit of statistical models.

Inhaltsangabe

New Introduction. 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.