Structural Equation Modeling : Concepts, Issues, and Applications

This largely nontechnical volume reviews some of the major issues facing researchers who wish to use structural equation modeling. Individual chapters present recent developments on specification, estimation and testing, statistical power, software comparisons and analyzing multitrait/multimethod data. Numerous examples of applications are given and attention is paid to the underlying philosophy of structural equation modeling and to writing up results from structural equation modeling analyses. Practical And Up-to-date, Structural Equation Modeling Includes Chapters On Major Aspects Of The Structural Equation Modeling Approach To Research Design And Data Analysis. The Chapters, Written By Internationally Recognized Leaders In The Development And Application Of Structural Equation Modeling, Target Graduate Students And Seasoned Researchers In The Social And Behavioral Sciences Who Wish To Understand The Basic Concepts And Issues Associated With The Structural Equation Modeling Approach As Well As Potential Applications To Research Problems. Although Technically Sound, The Chapters Are Primarily Nontechnical In Content And Style, A Characteristic That Makes The Volume An Excellent Introduction To The Structural Equation Modeling Approach For Readers Who Have A Firm Grasp On Traditional Inferential Statistics. The Structural Equation Modeling Approach: Basic Concepts And Fundamental Issues / Rick H. Hoyle -- Model Specification: Procedures, Strategies, And Related Issues / Robert C. Maccallum Estimates And Tests In Structural Equation Modeling / Chih-ping Chou -- Structural Equation Models With Nonnormal Variables: Problems And Remedies / Stephen G. West -- Evaluating Model Fit / Li-tze Hu --statical Power In Structural Equation Modeling / David Kaplan -- Objectivity And Reasoning In Science And Structural Equation Modeling / Stanley A. Mulaik -- One Application Of Structural Equation Modeling From Two Perspectives: Exploring The Eqs And Lisrel Strategies / Barbara M. Byne -- Writing About Structural Equation Models / Rick H. Hoyle -- Latent Variable Models Of Multitrait-multimethod Data / Herbert W. Marsh -- Sex-race Differences In Social Support And Depression In Older Low-income Adults / Jane A. Scott-lennox -- Modeling The Relation Of Personality Variables To Sympton Complaints: The Unique Role Of Negative Affectivity / Jay G. Hull -- Predictors Of Change In Antisocial Behavior During Elementary School For Boys / Mike Stoolmiller. Rick H. Hoyle, Editor. Includes Bibliographical References (p. 254-271) And Indexes. This book includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. It targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences. Contents: - Basic Concepts - Model Specification - Estimates and Tests - Nonnormal Variables - Evaluating Model Fit - Statistical Power - Objectivity and Reasoning - Exploring the EQS and LISREL Strategies - Writing about Structural Equation Models - Latent Variable Models - Sex-Race Differences in Social Support and Depression in Older Low-Income Adults - Modeling the Relation of Personality Variables to Symptom Complaints - Predictors of Change in Antisocial Behavior During Elementary School for Boys Practical and up-to-date, Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. Written by internationally recognized leaders in structural equation modeling, this book targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences. Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. The chapters, written by internationally recognised leaders in the development and application of structural equation modeling, target graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach as well as potential applications to research problems. Although technically sound, the chapters are primarily nontechnical in content and style. [Back cover, ed] Structural equation modeling (SEM) is a comprehensive statistical approach to testing hypotheses about relations among observed and latent variables.