Model Based Inference in the Life Sciences: A Primer on Evidence

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Overview

This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.

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Editorial Reviews

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From the reviews:

".… The writing style is pragmatic and appropriate for someone without advanced statistical training. Readers looking to recommend a book on information-criteria-based modeling to colleagues who are not statisticians, or looking to locate such a book for their libraries are likely to be satisfied with this book. " (Biometrics, December 2008, Brief Reports by the Editor)

"This … book provides an introduction to this approach of evidence-based inference. It is focused on advocating and teaching the approach. It includes some history and philosophy with the methods, and each chapter ends with exercises. … For those who are already familiar with model-based inference … it provides a more in-depth account of the information theoretical approach. For those who are new to model-based inference, it provides a good conceptual and technical introduction." (Glenn Suter, Integrated Environmental Assessment and Management, Vol. 5 (2), 2009)

"Readership: Researchers and graduate students in ecology and other life sciences. This monograph expounds ideas that the author has developed over many years with Burnham. It is heavily example-based, and aimed at working scientists. Examples are predominately from ecological studies. … This is an interesting and challenging … book." (John H. Maindonald, International Statistical Review, Vol. 77 (3), 2009)

“…Presents an information-theoretic approach to statistical inference…Well motivated, clearly written, and thought provoking for its targeted readership. …” (The American Statistician, February 2010, Vol. 64, No. 1)

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Product Details

  • ISBN-13: 9780387740737
  • Publisher: Springer New York
  • Publication date: 12/1/2007
  • Edition description: 1st ed. 2008
  • Pages: 184
  • Sales rank: 898,141
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.45 (d)

Table of Contents

Introduction: Science Hypotheses and Science Philosophy.- Data and Models.- Information Theory and Entropy.- Quantifying the Evidence About Science Hypotheses.- Multimodel Inference.- Advanced Topics.- Summary.

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