Ebook: Recent Developments on Structural Equation Models: Theory and Applications
- Tags: Psychology general, Econometrics, Business/Management Science general, Economic Theory, Statistics for Business/Economics/Mathematical Finance/Insurance
- Series: Mathematical Modelling: Theory and Applications 19
- Year: 2004
- Publisher: Springer Netherlands
- Edition: 1
- Language: English
- pdf
After Karl Jöreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
After Karl J?reskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
After Karl J?reskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
Content:
Front Matter....Pages i-xv
Statistical Power in PATH Models for Small Sample Sizes....Pages 1-11
SEM State Space Modeling of Panel Data in Discrete and Continuous Time and its Relationship to Traditional State Space Modeling....Pages 13-40
Thurstone’s Case V Model: A Structural Equations Modeling Perspective....Pages 41-67
Evaluating Uncertainty of Model Acceptability in Empirical Applications: A Replacement Approach....Pages 69-82
Improved Analytic Interval Estimation of Scale Reliability....Pages 83-93
A Component Analysis Approach Towards Multisubject Multivariate Longitudinal Data Analysis....Pages 95-119
Least Squares Optimal Scaling of Partially Observed Linear Systems....Pages 121-134
Multilevel Structural Equation Models: the Limited Information Approach and the Multivariate Multilevel Approach....Pages 135-149
Latent Differential Equation Modeling with Multivariate Multi-Occasion Indicators....Pages 151-174
Varieties of Causal Modeling: How Optimal Research Design Varies by Explanatory Strategy....Pages 175-196
Is it Possible to Feel Good and Bad at the Same Time? New Evidence on the Bipolarity of Mood-state Dimensions....Pages 197-220
Development of a Short Form of the Eysenck Personality Profiler via Structural Equation Modeling....Pages 221-239
Methodological Issues in the Application of the Latent Growth Curve Model....Pages 241-261
Modeling Longitudinal Data of an Intervention Study on Travel Model Choice: Combining Latent Growth Curves and Autoregressive Models.....Pages 263-293
Methods for Dynamic Change Hypotheses....Pages 295-335
Modeling Latent Trait-Change....Pages 337-357
Back Matter....Pages 359-360
After Karl J?reskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
Content:
Front Matter....Pages i-xv
Statistical Power in PATH Models for Small Sample Sizes....Pages 1-11
SEM State Space Modeling of Panel Data in Discrete and Continuous Time and its Relationship to Traditional State Space Modeling....Pages 13-40
Thurstone’s Case V Model: A Structural Equations Modeling Perspective....Pages 41-67
Evaluating Uncertainty of Model Acceptability in Empirical Applications: A Replacement Approach....Pages 69-82
Improved Analytic Interval Estimation of Scale Reliability....Pages 83-93
A Component Analysis Approach Towards Multisubject Multivariate Longitudinal Data Analysis....Pages 95-119
Least Squares Optimal Scaling of Partially Observed Linear Systems....Pages 121-134
Multilevel Structural Equation Models: the Limited Information Approach and the Multivariate Multilevel Approach....Pages 135-149
Latent Differential Equation Modeling with Multivariate Multi-Occasion Indicators....Pages 151-174
Varieties of Causal Modeling: How Optimal Research Design Varies by Explanatory Strategy....Pages 175-196
Is it Possible to Feel Good and Bad at the Same Time? New Evidence on the Bipolarity of Mood-state Dimensions....Pages 197-220
Development of a Short Form of the Eysenck Personality Profiler via Structural Equation Modeling....Pages 221-239
Methodological Issues in the Application of the Latent Growth Curve Model....Pages 241-261
Modeling Longitudinal Data of an Intervention Study on Travel Model Choice: Combining Latent Growth Curves and Autoregressive Models.....Pages 263-293
Methods for Dynamic Change Hypotheses....Pages 295-335
Modeling Latent Trait-Change....Pages 337-357
Back Matter....Pages 359-360
....