Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. _x000D_ _x000D_ SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. _x000D_ _x000D_ Features:_x000D_ _x000D_ _x000D_ Basic, intermediate, and advanced SEM topics _x000D_ _x000D_ _x000D_ Detailed applications, particularly relevant for health and medical scientists_x000D_ _x000D_ _x000D_ Topics and examples that are pertinent to both new and experienced SEM researchers_x000D_ _x000D_ _x000D_ Substantive issues in health and medicine in the context of SEM_x000D_ _x000D_ _x000D_ Both methodological and applied examples_x000D_ _x000D_ _x000D_ Numerous figures and diagrams to illustrate the examples_x000D_ _x000D_ _x000D_ As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales. _x000D_

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