Emphasizing causation as a functional relationship between variables, this book provides comprehensive coverage on the basics of SEM. It takes readers through the process of identifying, estimating, analyzing, and evaluating a range of models. The author discusses the history and philosophy of causality and its place in science and presents graph theory as a tool for the design and analysis of causal models. He explains how the algorithms in SEM are derived and how they work, covers various indices and tests for evaluating the fit of structural equation models to data, and explores recent research in graph theory, path tracing rules, and model evaluation.

An intermediate level text covering foundational ideas in statistics and their ecological application, including generalized linear and generalized mixed-effect models, as well as models allowing for mixtures, spatial or phylogenetic correlations, missing or censored data, and observational data; implemented in R and set within a contemporary research framework.

When the first edition of this Handbook was fields are likely to be hard reading, but anyone who wants to get in touch with the published in 1966 I scarcely gave thought to a future edition. Its whole purpose was to growing edges will find something to meet his inaugurate a radical new outlook on ex taste. perimental psychology, and if that could be Of course, this book will need teachers. As accomplished it was sufficient reward. In the it supersedes the narrow conceptions of 22 years since we have seen adequate-indeed models and statistics still taught as bivariate staggering-evidence that the growth of a new and ANOV A methods of experiment, in so branch of psychological method in science has many universities, those universities will need become established. The volume of research to expand their faculties with newly trained has grown apace in the journals and has young people. The old vicious circle of opened up new areas and a surprising increase obsoletely trained members turning out new of knowledge in methodology. obsoletely trained members has to be The credit for calling attention to the need recognized and broken. And wherever re for new guidance belongs to many members search deals with integral wholes-in per of the Society of Multivariate Experimental sonalities, processes, and groups-researchers Psychology, but the actual innervation is due will recognize the vast new future that to the skill and endurance of one man, John multivariate methods open up.

"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--

Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This book draws upon the best writing in a variety of fields to provide a comprehensive picture of contemporary work on this subject. This collection of articles stands alone as a course book on the causal modeling approach to theory construction and data analysis. There is a growing literature on causal models and structural systems of equations that crosscuts a number of different fields. However, much of this material remains widely scattered throughout the journal literature and varies considerably in terms of both level of difficulty and substantive application. This classic text by Blalock addresses and resolves this concern. The most systematic discussions of this general approach have appeared in the econometrics literature, where several general texts are available. However, many of these discussions are too technical for most sociologists, political scientists, scholars, and researchers who lack a strong background in mathematics. This book attempts to integrate a few of the less technical papers written by econometricians such as Koopmans, Wold, Strotz, and Fisher with discussions of causal approaches in the biological sciences and with relatively more exploratory treatments by sociologists and other social scientists.

Over the years, researchers have developed statistical methods to help them investigate and interpret issues of interest in many discipline areas. These methods range from descriptive to inferential to multivariate statistics. As the psychometrics measures in education become more complex, vigorous and robust methods were needed in order to represent research data efficiently. One such method is Structural Equation Modeling (SEM). SEM is a statistical technique that allows the simultaneous analysis of a series of structural equations. It also allows a dependent variable in one equation to become an independent variable in another equation. It is a comprehensive statistical approach to testing hypotheses about relations among observed and latent variables. SEM is commonly known as causal modeling, or path analysis, which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. As educational research questions become more complex, they need to be evaluated with more sophisticated tools. The pervasive use of SEM in the literature has shown that SEM has a potential to be of assistance to modern educational researchers. This book will bring together prominent educators and researchers from around the world to share their contemporary research on structural equation modeling in educational settings. The chapters provide information on recent trends and developments and effective applications of the different models to answer various educational research questions. This book is a critical and specialized source that describes recent advances in SEM in international academia.