Bruno Lecoutre

Cet ouvrage pluridisciplinaire est a la charniere de la psychologie cognitive et de la statistique. On y trouvera d'une part une analyse de la demarche et des attitudes des chercheurs face a l'inference statistique, d'autre part des propositions pour renouveler les pratiques statistiques, en les completant par des methodes (combinatoires et bayesiennes) mieux adaptees et aujourd'hui accessibles grace a l'informatique. Cet ouvrage s'adresse aux chercheurs, enseignants et utilisateurs de la statistique, tout particulierement en psychologie et en sciences humaines, qui y trouveront un texte de reference pour l'approche de la nouvelle ecole statistique de Paris."

This book explains the misuses and abuses of Null Hypothesis Significance Tests, which are reconsidered in light of Jeffreys’ Bayesian concept of the role of statistical inference, in experimental investigations. Minimizing the technical aspects, the studies focuses mainly on methodological contributions. The first part of the book gives an overview of the major approaches to statistical testing and an enlightening discussion of the philosophies of Fisher, Neyman-Pearson and Jeffrey. The conceptual and methodological implications of current practices of reporting effect sizes and confidence intervals are also examined and challenged. This sheds new light on the "significance testing controversy" and provides an appropriate Bayesian framework for a comprehensive approach to the analysis and interpretation of experimental data. The second part of the book provides concrete Bayesian routine procedures that bypass common misuses of significance testing and arereadily applicable in a wide range of real applications. This approach addresses the need for objective reporting of experimental data, that is acceptable to the scientific community. This is emphasized by the name fiducial (from the Latin fiducia = confidence). The fiducial Bayesian procedures provide the reader with a real opportunity to think sensibly about problems of statistical inference. This book prepares students and researchers to critically read statistical analyses reported in the literature and equips them with an appropriate alternative to the use of significance testing.

This book, with a foreword by the outstanding philosopher of science and mathematical psychologist Patrick Suppes of Stanford University, is the outgrowth of the work developed within the Groupe Math matiques et Psychologie, a research unit of the University Ren Descartes and CNRS (the French National Center for Scientific Research). New ways in statistical methodology are presented, which complement the familiar significance tests by new methods better suited to the researchers' objectives, in the first place, Bayesian methods. In mathematical statistics, Bayesian methods have made a breakthrough in the last few years, but those developments are still ignored by the current statistical methodology and practice. The present book is really the first one to fill this gap. This book is written for a large audience of researchers, statisticians and users of statistics in behavioral and social sciences, and contains both an analysis of the attitude of researchers toward statistical inference, and concrete proposals for improving statistical practice. The statistical consulting experience of the authors is centered around psychology and covers a broad range of subjects from social sciences to biostatistics. All methods developed by the authors are implemented in software.