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 for R, Stata, and Mplus.
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Product Details
Weight: 190g
Dimensions: 139 x 215mm
Publication Date: 21 Mar 2022
Publisher: SAGE Publications Inc
Publication City/Country: United States
Language: English
ISBN13: 9781544375137
About J. Micah RoosShawn Bauldry
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. Shawn Bauldry is an Associate Professor in the Department of Sociology at Purdue University. He received a Ph.D. in Sociology and an M.S. in Statistics from the University of North Carolina at Chapel Hill in 2012 and has previously taught at the University of Alabama at Birmingham. His research in applied statistics primarily focuses on the development of structural equation models. His research in sociology explores interrelationships between socioeconomic resources and health over the life course and across generations. His work has appeared in a variety of outlets including Sociological Methodology Sociological Methods & Research Psychological Methods Social Forces and Journal of Health and Social Behavior.