Measurement connects theoretical concepts to what is observable in the empirical world, and is fundamental to all social and behavioral research. In this volume, J. Micah Roos and Shawn Bauldry introduce a popular approach to measurement: Confirmatory Factor Analysis (CFA). As the authors explain, CFA is a theoretically informed statistical framework for linking multiple observed variables to latent variables that are not directly measurable. The authors begin by defining terms, introducing notation, and illustrating a wide variety of measurement models with different relationships between latent and observed variables. They proceed to a thorough treatment of model estimation, followed by a discussion of model fit. Most of the volume focuses on measures that approximate continuous variables, but the authors also devote a chapter to categorical indicators. Each chapter develops a different example (sometimes two) covering topics as diverse as racist attitudes, theological conservatism, leadership qualities, psychological distress, self-efficacy, beliefs about democracy, and Christian nationalism drawn mainly from national surveys. Data to replicate the examples are available on a companion website, along with code in R, Stata, and Mplus.
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J. Micah Roos is an associate professor of sociology at Virginia Polytechnic Institute and State University. His research interests include knowledge, science, religion, culture, stratification, measurement, racial attitudes, and quantitative methods. He ties these interests together through a quantitative, measurement approach to the sociology of knowledge and culture, with a focus on stratification along the early life course. Another strand of his work involves applying techniques in confirmatory factor analysis to the problem of differential item functioning or item-level bias. He holds a PhD in Sociology from the University of North Carolina at Chapel Hill.
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