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Cover: 9780387945163 | Basic Principles of Structural Equation Modeling | Ralph O. Mueller
Bild: 9780387945163 | Basic Principles of Structural Equation Modeling | Ralph O. Mueller
Cover: 9780387945163 | Basic Principles of Structural Equation Modeling | Ralph O. Mueller
Bild: 9780387945163 | Basic Principles of Structural Equation Modeling | Ralph O. Mueller
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Basic Principles of Structural Equation Modeling
An Introduction to LISREL and EQS
Buch von Ralph O. Mueller
Sprache: Englisch

46,95 €*

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Beschreibung
During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g. , Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail­ ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a,b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre­ sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo­ retical and empirical aspects of behavioral research.
During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g. , Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail­ ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a,b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre­ sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo­ retical and empirical aspects of behavioral research.
Inhaltsverzeichnis
1 Linear Regression and Classical Path Analysis.- Overview and Key Points.- Linear Ordinary Least Squares Regression.- Classical Path Analysis.- Summary.- Exercises.- Recommended Readings.- 2 Confirmatory Factor Analysis.- Overview and Key Points.- Specification and Identification of a CFA Model.- Data-Model Fit.- Model Modification.- Validity and Reliability from a CFA Perspective.- Summary.- Exercises.- Recommended Readings.- 3 General Structural Equation Modeling.- Overview and Key Points.- Specification and Identification of a General Structural Equation Model.- The Direct, Indirect, and Total Structural Effect Components.- Parameter Estimation.- The Structural Equation Modeling Process: An Illustrated Review and Summary.- Conclusion.- Exercises.- Recommended Readings.- Appendix A.- The SIMPLIS Command Language.- Overview and Key Points.- Appendix B.- Location, Dispersion, and Association.- Overview and Key Points.- Statistical Expectation.- A Measure of a Distribution's Location.- A Measure of a Distribution's Dispersion.- A Measure of Association Between Two Variables.- Statistical Standardization.- Standardized Variables.- A Standardized Measure of Association Between Two Variables.- Recommended Readings.- Appendix C.- Matrix Algebra.- Overview and Key Points.- Some Basic Definitions.- Algebra with Matrices.- The Variance/Covariance Matrix.- Recommended Readings.- Appendix D.- Descriptive Statistics for the SES Analysis.- Appendix E.- References.
Details
Erscheinungsjahr: 1995
Fachbereich: Analysis
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Reihe: Springer Texts in Statistics
Inhalt: xxviii
232 S.
ISBN-13: 9780387945163
ISBN-10: 0387945164
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Mueller, Ralph O.
Hersteller: Springer New York
Springer US, New York, N.Y.
Springer Texts in Statistics
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 241 x 160 x 20 mm
Von/Mit: Ralph O. Mueller
Erscheinungsdatum: 20.10.1995
Gewicht: 0,571 kg
Artikel-ID: 102222759
Inhaltsverzeichnis
1 Linear Regression and Classical Path Analysis.- Overview and Key Points.- Linear Ordinary Least Squares Regression.- Classical Path Analysis.- Summary.- Exercises.- Recommended Readings.- 2 Confirmatory Factor Analysis.- Overview and Key Points.- Specification and Identification of a CFA Model.- Data-Model Fit.- Model Modification.- Validity and Reliability from a CFA Perspective.- Summary.- Exercises.- Recommended Readings.- 3 General Structural Equation Modeling.- Overview and Key Points.- Specification and Identification of a General Structural Equation Model.- The Direct, Indirect, and Total Structural Effect Components.- Parameter Estimation.- The Structural Equation Modeling Process: An Illustrated Review and Summary.- Conclusion.- Exercises.- Recommended Readings.- Appendix A.- The SIMPLIS Command Language.- Overview and Key Points.- Appendix B.- Location, Dispersion, and Association.- Overview and Key Points.- Statistical Expectation.- A Measure of a Distribution's Location.- A Measure of a Distribution's Dispersion.- A Measure of Association Between Two Variables.- Statistical Standardization.- Standardized Variables.- A Standardized Measure of Association Between Two Variables.- Recommended Readings.- Appendix C.- Matrix Algebra.- Overview and Key Points.- Some Basic Definitions.- Algebra with Matrices.- The Variance/Covariance Matrix.- Recommended Readings.- Appendix D.- Descriptive Statistics for the SES Analysis.- Appendix E.- References.
Details
Erscheinungsjahr: 1995
Fachbereich: Analysis
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Reihe: Springer Texts in Statistics
Inhalt: xxviii
232 S.
ISBN-13: 9780387945163
ISBN-10: 0387945164
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Mueller, Ralph O.
Hersteller: Springer New York
Springer US, New York, N.Y.
Springer Texts in Statistics
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 241 x 160 x 20 mm
Von/Mit: Ralph O. Mueller
Erscheinungsdatum: 20.10.1995
Gewicht: 0,571 kg
Artikel-ID: 102222759
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