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.
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.
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.
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.
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