Tenko Raykov

Bio: Tenko Raykov is an academic researcher from Michigan State University. The author has contributed to research in topics: Latent variable model & Interval estimation. The author has an hindex of 39, co-authored 202 publications receiving 9521 citations. Previous affiliations of Tenko Raykov include University of Melbourne & Fordham University.

A First Course in Structural Equation Modeling

Abstract: In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one.Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner’s guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software.Highlights of the Second Edition include:• Review of latent change (growth) analysis models at an introductory level• Coverage of the popular Mplus program• Updated examples of LISREL and EQS• Downloadable resources that contains all of the text’s LISREL, EQS, and Mplus examples.A First Course in Structural Equation Modeling is intended as an introductory book for students and researchers in psychology, education, business, medicine, and other applied social, behavioral, and health sciences with limited or no previous exposure to SEM. A prerequisite of basic statistics through regression analysis is recommended. The book frequently draws parallels between SEM and regression, making this prior knowledge helpful.

Estimation of composite reliability for congeneric measures.

Abstract: A structural equation model is described that permits estimation of the reliability index and coefficient of a composite test for congeneric measures. The method is also helpful in exploring the fa...

An Introduction to Applied Multivariate Analysis

Abstract: This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe

Introduction to Psychometric Theory

Abstract: 1. Measurement, Measuring Instruments, and Psychometric Theory. 2. Basic Statistical Concepts and Relationships. 3. An Introduction to Factor Analysis. 4. Introduction to Latent Variable Modeling and Confirmatory Factor Analysis. 5. Classical Test Theory. 6. Reliability. 7. Procedures for Estimating Reliability. 8. Validity. 9. Generalizability Theory. 10. Introduction to Item Response Theory. 11. Fundamentals and Models of Item Response Theory. Chapter Notes. Appendix. A Brief Introduction to Some Graphics Applications of R in Item Response Modeling.

Scale Reliability, Cronbach's Coefficient Alpha, and Violations of Essential Tau-Equivalence with Fixed Congeneric Components.

Abstract: The population discrepancy between Cronbach's Coefficient Alpha and scale reliability with fixed congeneric measures, uncorrelated errors, and sampling of subjects is studied. This difference is expressed in terms of individual component violations of the assumption of essential T-equivalence that is necessary and sufficient for Alpha to equal composite reliability. An upper bound of the discrepancy is obtained and its magnitude assessed in practical contexts of informed scale development. As an alternative when the difference may be considerable, a latent variable model is recommended for estimating scale reliability.

Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models

Abstract: Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

Using Multivariate Statistics

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Confirmatory Factor Analysis for Applied Research

Abstract: "With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages"--

Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures.

Abstract: For structural equation models, a huge variety of fit indices has been developed. These indices, however, can point to conflicting conclusions about the extent to which a model actually matches the observed data. The present article provides some guidelines that should help applied researchers to evaluate the adequacy of a given structural equation model. First, as goodness-of-fit measures depend on the method used for parameter estimation, maximum likelihood (ML) and weighted least squares (WLS) methods are introduced in the context of structural equation modeling. Then, the most common goodness-of-fit indices are discussed and some recommendations for practitioners given. Finally, we generated an artificial data set according to a "true" model and analyzed two misspecified and two correctly specified models as examples of poor model fit, adequate fit, and good fit.