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. 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.

Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors are internationally renowned experts in their respective areas. - Contributors are internationally renowned experts in their respective areas - Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research - Methods for assessing Biomarkers, analysis of competing risks - Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs - Structural equations modelling and longitudinal data analysis

This volume, representing a compilation of authoritative reviews on a multitude of uses of statistics in epidemiology and medical statistics written by internationally renowned experts, is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. While the use of statistics in these fields has a long and rich history, explosive growth of science in general and clinical and epidemiological sciences in particular have gone through a see of change, spawning the development of new methods and innovative adaptations of standard methods. Since the literature is highly scattered, the Editors have undertaken this humble exercise to document a representative collection of topics of broad interest to diverse users. The volume spans a cross section of standard topics oriented toward users in the current evolving field, as well as special topics in much need which have more recent origins. This volume was prepared especially keeping the applied statisticians in mind, emphasizing applications-oriented methods and techniques, including references to appropriate software when relevant.· Contributors are internationally renowned experts in their respective areas· Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research· Methods for assessing Biomarkers, analysis of competing risks· Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs· Structural equations modelling and longitudinal data analysis

This comprehensive, yet accessible, text demystifies the challenging area of competence assessement in medicine and the health sciences, providing a clear framework and the tools for anyone working or studying in this area. Written by a single, highly experienced, author, the content benefits from uniformity of style and is supported and enhanced by a range of pedagogic features including cases, questions and summaries. Essential reading for all students and practitioners of medical education, it will also be an invaluable guide for allied health professionals and psychologists with a general interest in assessment, evaluation and measurement and a useful library reference.

This book is comprehensive with most of its contents following the recommendations of international health and medical informatics associations and societies. To this extent it covers the areas of healthcare and medical information systems, management of healthcare and medical information systems, healthcare/medical information systems supporting patients and the public, healthcare/medical networking and care sharing, medical imaging and 3D/4D surgical visualization, design and analysis of health/medical records, health/medical data representation and analysis, simulation and modeling in healthcare, and health and medical informatics education. The book provides an excellent professional development resource for educators and practitioners on the state-of-the-art Health and Medical Informatics. It covers many areas and topics of Health and Medical Informatics and contributes toward the enhancement of the community outreach and engagement component of Health and Medical Informatics. Various techniques, methods, and approaches adopted by Health and Medical Informatics experts in the field are introduced. Furthermore, it provides detailed explanation of the Health and Medical Informatics concepts that are aptly reinforced by applications and some practical examples and a road map of future trends that are suitable for innovative Health and Medical Informatics.

Issues in Orthopedics and Occupational and Sports Medicine: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Orthopedics and Occupational and Sports Medicine. The editors have built Issues in Orthopedics and Occupational and Sports Medicine: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Orthopedics and Occupational and Sports Medicine in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Orthopedics and Occupational and Sports Medicine: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

This edited volume brings together some of the best papers from the 2022 Conference on Partial Least Squares Structural Equation Modeling (PLS-SEM), held at the Babeș-Bolyai University, Cluj, Romania. The volume seeks to expand the current research on PLS-SEM and promote the method’s application in the scientific community. It gathers research from scholars in many different fields who work on the advancement of PLS-SEM and who apply the method to explain and predict behavioral phenomena. Researchers today can draw on a wide array of different PLS-SEM-based algorithms, complementary methods, and model evaluation metrics. Tying in with these developments, the first part of this book documents methodological advances of PLS-SEM, which extend the researchers’ current toolbox of methods. The following parts demonstrate state-of-the-art applications of PLS-SEM in various fields such as consumer behavior, hospitality, human resource management, entrepreneurship, and organizational behavior. Special emphasis is placed on studies that apply complementary methods to offer a more nuanced analysis of the research questions.

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.

Concise Encyclopedia of Biostatistics for Medical Professionals focuses on conceptual knowledge and practical advice rather than mathematical details, enhancing its usefulness as a reference for medical professionals. The book defines and describes nearly 1000 commonly and not so commonly used biostatistical terms and methods arranged in alphabetical order. These range from simple terms, such as mean and median to advanced terms such as multilevel models and generalized estimating equations. Synonyms or alternative phrases for each topic covered are listed with a reference to the topic.