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