03650cam a2200517Ki 45000010014000000030008000140050017000220060019000390070015000580080041000730400035001140200035001490200032001840200035002160200032002510200047002830200044003300200041003740200038004150350022004530350024004750500021004990720025005200720025005450720016005700820020005861000034006062450114006402640049007542640011008033000058008143360026008723370026008983380036009244900044009605201702010045880047027066500030027536500062027836500037028457000030028827000029029128560072029418560102030139990017031159780203701133FlBoTFG20260210180842.0m     o  d        cr cnu---unuuu210208t20212021flua   fo     000 0 eng d  aOCoLC-PbengerdaepncOCoLC-P  a9781351329729qelectronic book  a1351329723qelectronic book  a9780203701133qelectronic book  a0203701135qelectronic book  a9781351329705qelectronic bookqMobipocket  a1351329707qelectronic bookqMobipocket  a9781351329712qelectronic bookqEPUB  a1351329715qelectronic bookqEPUB  a(OCoLC)1240718054  a(OCoLC-P)1240718054 4aRA407b.G86 2021 7aMATx0290002bisacsh 7aMEDx0900002bisacsh 7aJMB2bicssc04a610.1/519532231 aGunzler, Douglas D.,eauthor.10aStructural equation modeling for health and medicine /cDouglas D. Gunzler, Adam T. Perzynski, Adam C. Carle. 1aBoca Raton, FL :bChapman & Hall/CRC,c2021. 4c©2021  a1 online resource :billustrations (black and white).  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier1 aChapman & Hall/CRC biostatistics series  aStructural 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. 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. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples 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.  aOCLC-licensed vendor bibliographic record. 0aMedical statistics.94881 7aMATHEMATICS / Probability & Statistics / General2bisacsh 7aMEDICAL / Biostatistics2bisacsh1 aPerzynski, Adam,eauthor.1 aCarle, Adam C.,eauthor.403Taylor & Francisuhttps://www.taylorfrancis.com/books/9780203701133423OCLC metadata license agreementuhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf  c92707d92706