Structural Equation Modeling: Applications in Ecological and Evolutionary Biology

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9780521104029: Structural Equation Modeling: Applications in Ecological and Evolutionary Biology

This book presents an introduction to the methodology of structural equation modeling, illustrates its use, and goes on to argue that it has revolutionary implications for the study of natural systems. A major theme of this book is that we have, up to this point, attempted to study systems primarily using methods (such as the univariate model) that were designed only for considering individual processes. Understanding systems requires the capacity to examine simultaneous influences and responses. Structural equation modeling (SEM) has such capabilities. It also possesses many other traits that add strength to its utility as a means of making scientific progress. In light of the capabilities of SEM, it can be argued that much of ecological theory is currently locked in an immature state that impairs its relevance. It is further argued that the principles of SEM are capable of leading to the development and evaluation of multivariate theories of the sort vitally needed for the conservation of natural systems. Supplementary information can be found at the authors website, - Details why multivariate analyses should be used to study ecological systems - Exposes unappreciated weakness in many current popular analyses - Emphasises the future methodological developments needed to advance our understanding of ecological systems

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Book Description:

Structural equation modeling (SEM) is a statistical methodology which, in this book, is applied to research questions in ecology and evolutionary biology. The book differs from others on SEM because it is written specifically for biologists with an approach that is adapted to their statistical knowledge and background. This text will serve as a valuable resource for both learning and teaching the SEM methodology. Data sets and programs that are presented in the book can also be downloaded from a web site to assist the learning process.

About the Author:

Bruce Pugesek is a research statistician in the U.S. Department of the Interior and is adjunct professor in the Department of Comparative Biomedical Sciences at The Louisiana State University.

Adrian Tomer is an Associate Professor at the Department of Psychology at Shippensburg University, Pennsylvania, where he teaches the psychology of aging and developmental psychology.

Alexander von Eye is a Professor in the Department of Psychology at Michigan State University.

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