Keren G., Lewis C. (Eds.) Handbook for Data Analysis in the Behavioral Sciences: Methodological Issues

NY: Taylor&Francis, 1992. — 584 p. — ISBN: 0805810935, 978-0805810936.This book constitutes a considerable and elaborated revision of Statistical and Methodological Issues in Psychology and Social Sciences Research published in 1982. Some chapters from the previous book have been substantially revised (these are marked in the table of contents by an asterisk). A few chapters are based on journal articles that have been specifically revised to accommodate the book.) Most of the chapters, however, are original contributions to this edition.
Our emphasis on the cognitive facet has another aspect, namely the tendency of practitioners to view and apply methodological and statistical methods in a mechanical and technical manner. We believe that analysis and explanation of empirical data requires creativity as well as judgments (as is reflected explicitly in many chapters in this book). Data as well as results of statistical analysis can be interpreted in different ways. In fact, the initial decision of which particular method or statistical technique is most appropriate requires careful and meticulous considerations. We deliberately chose a broad spectrum of methods, some of which are known to be conflicting (e.g., Bayesian vs. classical statistics). We are also aware that the views expressed by different authors may occasionally be incompatible. The decision of which method to use, how, and when, is, in our
opinion, part of the researcher's task. We believe there is not always one right approach or method, and the final choice depends on the particular question the researcher wants to address, the nature of the data, and the larger context in which it was collected. The choice of which method is the appropriate one under given circumstances is part of what constitutes the art of the scientific inquiry.Models and measurement
William K. Estes
Mathematical Models in Psychology
Neil A. Macmillan
Signal Detection Theory as Data Analysis Method and Psychological Decision Model
Norman Cliff
What Is and Isn't Measurement
Lawrence E. Jones and Laura M. Koehly
Multidimensional Scaling
Glenn Shafer
Can the Various Meanings of Probability Be Reconciled?Methodological issues
Ronald C. Serlin and Daniel K. Lapsley
Rational Appraisal of Psychological Research and the Good-Enough Principle
Donald MacKay
The Theoretical Epistemology: A New Perspective on Some Long-Standing Methodological Issues in Psychology
Gideon Keren
Between- or Within-Subjects Design: A Methodological Dilemma
Paul W. Holland
Which Comes First, Cause or Effect?
Nancy Brenner-Golomb
R. A. Fisher's Philosophical Approach to Inductive InferenceIntuitive statistcs
Gerd Gigerenzer
The Superego, the Ego, and the Id in Statistical Reasoning
Amos Tversky and Daniel Kahneman
Belief in the Law of Small Numbers
Robyn M. Dawes, David Faust, and Paul E. Meehl
Statistical Prediction Versus Clinical Prediction: Improving What Works
Maya Bar-Hillel and Willem A. Wagenaar
The Perception of Randomness
Peter J. Pashley
On Generating Random SequencesHypothesis testing, power, and effect size
Anthony G. Greenwald
Consequences of Prejudice Against the Null Hypothesis
Paul Pollard
How Significant Is "Significance"?
Maurice Tatsuoka
Effect Size
Donald W. Zimmerman and Bruno D. Zumbo
The Relative Power of Parametric and Nonparametric Statistical Methods
Robert Rosenthal
Cumulating Evidence