Statistical methodology is often conceived by social scientists in a technical manner; they use it for support rather than for illumination. This two-volume set attempts to provide some partial remedy to the problems that have led to this state of affairs. Both traditional issues, such as analysis of variance and the general linear model, as well as more novel methods like exploratory data analysis, are included. The editors aim to provide an updated survey on different aspects of empirical research and data analysis, facilitate the understanding of the internal logic underlying different methods, and provide novel and broader perspectives beyond what is usually covered in traditional curricula.
review for Volume I:
"…the chapter authors are leaders in their areas of expertise; the coverage in each chapter is comprehensive and well considered. The book offers an overview of methodological concerns that is wide-ranging and state-of-the-art….Strongly recommended for libraries that provide coverage of advanced topics in statistics and methodology in the social and behavioral sciences….this volume will become a classic reference source."
review for Volume II:
"…chapters tend to be well written and comprehensive….well constructed and produced….strongly recommended for libraries that provide coverage of advanced topics in statistics and methodology in the social and behavioral sciences….will become a classic reference source."
"…these two volumes contain a wealth of information, concisely summarized with excellent reference sections."
"…the editors are to be commended for their intrepid venture. Both books include provocative material, as well as 'helper' kinds of information….I found all of the chapters to be highly informative….psychological methodologists may content themselves with Keren and Lewis's two volumes as the basis for a vibrant seminar or discussion group on methodology and statistics in the behavioral sciences."
"I can positively recommend it to anyone who is worried about the assumptions and underlying bases of the statistics used by psychologists…"
—British Journal of Mathematical and Statistical Psychology
"The two volumes present an excellent survey of research statistics and data analysis written by eminent researchers expressly to make methodological and statistical developments available to those with limited technical skills. Material is clearly presented, applications are emphasized, provisos stated, and copious references given for each topic….This is the single best available source of information on statistical methods and applications, coupled with equally useful thought-provoking criticisms ranging from technical to psychological to philosophical."
—Perceptual and Motor Skills
"We praise these volumes… Editing such volumes is without question an accomplishment….We…congratulate [the editors] for attempting the unthinkable, and doing a good job at it."
—Journal of the American Statistical Association
Volume I: Methodological Issues. Contents: Preface. Part I: Models and Measurement. W.K. Estes, Mathematical Models in Psychology. N.A. Macmillan, Signal Detection Theory as Data Analysis Method and Psychological Decision Model. N. Cliff, What Is and Isn't Measurement. L.E. Jones, L.M. Koehly, Multidimensional Scaling. G. Shafer, Can the Various Meanings of Probability Be Reconciled? Part II: Methodological Issues. R.C. Serlin, D.K. Lapsley, Rational Appraisal of Psychological Research and the Good-Enough Principle. D. MacKay, The Theoretical Epistemology: A New Perspective on Some Long-Standing Methodological Issues in Psychology. G. Keren, Between- or Within-Subjects Design: A Methodological Dilemma. P.W. Holland, Which Comes First, Cause or Effect? N. Brenner-Golomb, R.A. Fisher's Philosophical Approach to Inductive Inference. Part III: Intuitive Statistics. G. Gigerenzer, The Superego, the Ego, and the Id in Statistical Reasoning. A. Tversky, D. Kahneman, Belief in the Law of Small Numbers. R.M. Dawes, D. Faust, P.E. Meehl, Statistical Prediction Versus Clinical Prediction: Improving What Works. M. Bar-Hillel, W.A. Wagenaar, The Perception of Randomness. P.J. Pashley, On Generating Random Sequences. Part IV: Hypothesis Testing, Power, and Effect Size. A.G. Greenwald, Consequences of Prejudice Against the Null Hypothesis. P. Pollard, How Significant Is "Significance"? M. Tatsuoka, Effect Size. D.W. Zimmerman, B.D. Zumbo, The Relative Power of Parametric and Nonparametric Statistical Methods. R. Rosenthal, Cumulating Evidence. Volume 2: Statistical Issues. Contents: Preface. Part I: Analysis of Variance and Multiple Regression. M. Tatsuoka, Elements of the General Linear Model. R. Zwick, Pairwise Comparison Procedures for One-Way Analysis of Variance Designs. C. Lewis, Analyzing Means From Repeated Measures Data. G. Keren, A Balanced Approach to Unbalanced Designs. N.M. Timm, MANOVA and MANCOVA: An Overview. J. Cohen, Set Correlation. Part II: Bayesian Statistics. R.L. Winkler, Bayesian Statistics: An Overview. C. Lewis, Bayesian Methods for the Analysis of Variance. Part III: Categorical Data and the Analysis of Frequencies. S.S. Brier, Analysis of Categorical Data. K.L. Delucchi, On the Use and Misuse of Chi-Square. B.S. Everitt, Some Aspects of the Analysis of Categorical Data. Part IV: Other Topics. A.F. Smith, D.A. Prentice, Exploratory Data Analysis. H. Wainer, D. Thissen, Graphical Data Analysis. R.M. Church, Uses of Computers in Psychological Research. G.R. Loftus, Computer Simulation: Some Remarks on Theory in Psychology. R.H. Rushe, J.M. Gottman, Essentials in the Design and Analysis of Time-Series Experiments.