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Abstract
Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.
Publication type | Book chapter |
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Publication Subtype | Book Chapter |
Title | Structural equation modeling: Building and evaluating causal models |
Chapter | 8 |
Year Published | 2015 |
Language | English |
Publisher | Oxford University Press |
Publisher location | Oxford, UK |
Contributing office(s) | National Wetlands Research Center |
Description | 32 p. |
Larger Work Type | Book |
Larger Work Subtype | Monograph |
Larger Work Title | Ecological statistics: contemporary theory and application |
First page | 168 |
Last page | 199 |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |