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The Nature of Scientific Evidence

Statistical, Philosophical, and Empirical Considerations

An exploration of the statistical foundations of scientific inference, The Nature of Scientific Evidence asks what constitutes scientific evidence and whether scientific evidence can be quantified statistically. Mark Taper, Subhash Lele, and an esteemed group of contributors explore the relationships among hypotheses, models, data, and inference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence. Informed by interdisciplinary discussions among scientists, philosophers, and statisticians, they propose a new "evidential" approach, which may be more in keeping with the scientific method. The Nature of Scientific Evidence persuasively argues that all scientists should care more about the fine points of statistical philosophy because therein lies the connection between theory and data.

Though the book uses ecology as an exemplary science, the interdisciplinary evaluation of the use of statistics in empirical research will be of interest to any reader engaged in the quantification and evaluation of data.

448 pages | 25 line drawings, 6 tables | 6 x 9 | © 2004

Biological Sciences: Ecology

Mathematics and Statistics

Philosophy of Science

Reviews

"The book is a rare find: a source that could be used in graduate seminars in statistics, philosophy, or biology....It is brimming with ideas....It deserves a read by everyone."

Marc Mangel | Science

"This is a challenging, stimulating, and important book Although some of the chapters are not for the statistically naive, all are thorough and provocative....The Nature of Scientific Evidence should be read by all ecologists who interpret data as evidence for or against specific hypotheses."

Gerry Quinn | Trends in Ecology and Evolution

"The Nature of Scientific Evidence may well be viewed as a landmark publication in years to come, one that was the precursor to a new set of statistical methodologies based on evidence and likelihood. . . . We unreservedly recommend it to every ecologist wanting to understand more about the relationship between logic, evidence, analysis and inference – which, after all, constitutes the essence of the scientific method."

Graeme Hastwell and S. Raghu | Austral Ecology

"The book is important not because of its specific content, but because of what it represents: a cross-disciplinary dialogue that addresses key issues in data analysis."

Nicholas J. Gotelli | Ecoscience

"It is precisely because this nicely and carefully edited book will provide more questions than answers that it deserves to be read and discussed by the wide audience of statisticians, philosophers of science, and scientists to whom it addresses the important problem of the evaluation of scientific evidence."

Pablo Inchausti | Quarterly Review of Biology

"This volume is a wonderful guide helping ecologists to understand many of the statistical nuances as well as an introduction to some deep-rooted methodological and philosophical issues in data analysis. . . . An important and necessary discussion that ecologists need to have."

Marc W. Cadotte | Biodiversity Conservation

Table of Contents

Foreword by C. R. Rao
Preface
Part 1: Scientific Process
Overview
Mark L. Taper and Subhash R. Lele
1: A Brief Tour of Statistical Concepts
Nicholas Lewin-Koh, Mark L. Taper, and Subhash R. Lele
2: Models of Scientific Inquiry and Statistical Practice: Implications for the Structure of Scientific Knowledge
Brian A. Maurer
2.1: Commentary
Prasanta S. Bandyopadhyay and John G. Bennett
2.2: Commentary
Mark L. Wilson
2.3: Rejoinder
Brian A. Maurer
3: Experiments, Observations, and Other Kinds of Evidence
Samuel M. Scheiner
3.1: Commentary
Marie-Josée Fortin
3.2: Commentary
Manuel C. Molles, Jr.
3.3: Rejoinder
Samuel M. Scheiner
Part 2: Logics of Evidence
Overview
V. P. Godambe
4: An Error-Statistical Philosophy of Evidence
Deborah G. Mayo
4.1: Commentary
Earl D. McCoy
4.2: Commentary
George Casella
4.3: Rejoinder
Deborah G. Mayo
5: The Likelihood Paradigm for Statistical Evidence
Richard Royall
5.1: Commentary
D. R. Cox
5.2: Commentary
Martin Curd
5.3: Rejoinder
Richard Royall
6: Why Likelihood?
Malcolm Forster and Elliott Sober
6.1: Commentary
Michael Kruse
6.2: Commentary
Robert J. Boik
6.3: Rejoinder
Malcolm Forster and Elliott Sober
7: Evidence Functions and the Optimality of the Law of Likelihood
Subhash R. Lele
7.1: Commentary
Christopher C. Heyde
7.2: Commentary
Paul I. Nelson
7.3: Rejoinder
Subhash R. Lele
Part 3: Realities of Nature
Overview
Mark S. Boyce
8: Whole-Ecosystem Experiments: Replication and Arguing from Error
Jean A. Miller and Thomas M. Frost
8.1: Commentary
William A. Link
8.2: Commentary
Charles E. McCulloch
8.3: Rejoinder
Jean A. Miller
9: Dynamical Models as Paths to Evidence in Ecology
Mark L. Taper and Subhash R. Lele
9.1: Commentary
Steven Hecht Orzack
9.2: Commentary
Philip M. Dixon
9.3: Rejoinder
Mark L. Taper and Subhash R. Lele
10: Constraints on Negative Relationships: Mathematical Causes and Ecological Consequences
James H. Brown, Edward J. Bedrick, S. K. Morgan Ernest, Jean-Luc E. Cartron, and Jeffrey F. Kelly
10.1: Commentary
Robert D. Holt and Norman A. Slade
10.2: Commentary
Steve Cherry
10.3: Rejoinder
James H. Brown, Edward J. Bedrick, S. K. Morgan Ernest, Jean-Luc E. Cartron, and Jeffrey F. Kelly
Part 4: Science, Opinion, and Evidence
Overview
Mark L. Taper and Subhash R. Lele
11: Statistics and the Scientific Method in Ecology
Brian Dennis
11.1: Commentary
Charles E. McCulloch
11.2: Commentary
Aaron M. Ellison
11.3: Rejoinder
Brian Dennis
12: Taking the Prior Seriously: Bayesian Analysis without Subjective Probability
Daniel Goodman
12.1: Commentary
Nozer D. Singpurwalla
12.2: Rejoinder
Daniel Goodman
13: Elicit Data, Not Prior: On Using Expert Opinion in Ecological Studies
Subhash R. Lele
13.1: Commentary
R. Cary Tuckfield
13.2: Commentary
Lance A. Waller
13.3: Rejoinder
Subhash R. Lele
Part 5: Models, Realities, and Evidence
Overview
Mark L. Taper and Subhash R. Lele
14: Statistical Distances as Loss Functions in Assessing Model Adequacy
Bruce G. Lindsay
14.1: Commentary
D. R. Cox
14.2: Commentary
Stephen P. Ellner
14.3: Rejoinder
Bruce G. Lindsay
15: Model Identification from Many Candidates
Mark L. Taper
15.1: Commentary
Isabella Verdinelli and Larry Wasserman
15.2: Commentary
Hamparsum Bozdogan
15.3: Rejoinder
Mark L. Taper
Part 6: Conclusion
16: The Nature of Scientific Evidence: A Forward-Looking Synthesis
Mark L. Taper and Subhash R. Lele
List of Contributors
Index

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