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The book came about due to a series of workshops and panels on structural equation modeling (SEM) we presented at national health services research and medical decisionmaking meetings. Our initial workshop goal was to satisfy the curiosity of graduate students, faculty, industry professionals and other attendees and help them gain a solid understanding of the introductory principles of SEM. However, it became clear to us during both question and answer portions and informal post-lecture discussion that many attendees still needed a deeper understanding of how to apply these techniques with particular health and medical studies in mind. The problems and questions from our health science audience did not follow “linearly” from the typical introductory SEM examples for the social sciences. A classic example that appears often in SEM introductions, manuals and tutorials describes the relationships between alienation and background variables such as education and occupation. While concepts such as alienation are familiar to many sociologists and other social scientists, they may be less helpful at the introductory stage for researchers studying health and medicine.
Health and medical researchers use a wide variety of data sources, including complex and messy real-world data. Study designs are also highly variable. Translating a conceptual model into a formal structural equation model under the boundaries of a study can be diffcult in practice. Likewise, output from software for the analysis of structural equation models (SEMs) commonly requires thorough review and interpretation. Careful consideration of theory, logic and prior literature is mandatory (as with all SEM research). Thus, our workshops and panels over time became adapted to showcase the methods for more
nuanced examples in health and medicine.
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