Structural Modeling by Example offers a comprehensive overview of the application of structural equation models in the social and behavioural sciences and in educational research.
Structural Modeling by Example offers a comprehensive overview of the application of structural equation models in the social and behavioural sciences and in educational research.
Preface; List of contributors; 1. Introduction Peter Cuttance and Russell Ecob; 2. An overview of structural equation modeling Russell Ecob and Peter Cuttance; 3. Field dependence and the differentiation of neurotic syndromes Katharine R. Parkes; 4. High school seniors' reports of parental socioeconomic status: black-white differences Lee M. Wolfle; 5. Modeling the hierarchical structure of learning Peter W. Hill; 6. A study of longitudinal causal models comparing gain score analysis with structural equation approaches Leslie Hendrickson and Barnie Jones; 7. Some structural equation models of sibling resemblance in educational attainment and occupational status Robert M. Hauser and Peter A. Mossel; 8. Applications of structural equation modeling to longitudinal educational data Russell Ecob; 9. The robustness of maximum likelihood estimation in structural equation models Anne Boomsma; 10. An inquiry into the effects of outliers on estimates of a structural equation model of basic skills assessment Joan K. Gallini and Jim F. Casteel; 11. Testing structural equation models W. E. Saris, J. Den Ronden and A. Satorra; 12. LISREL models for inequality constraints in factor and regression analysis Henk Kelderman; 13. Issues and problems in the application of structural equation models Peter Cuttance; Appendix; Glossary; Index.
Preface; List of contributors; 1. Introduction Peter Cuttance and Russell Ecob; 2. An overview of structural equation modeling Russell Ecob and Peter Cuttance; 3. Field dependence and the differentiation of neurotic syndromes Katharine R. Parkes; 4. High school seniors' reports of parental socioeconomic status: black-white differences Lee M. Wolfle; 5. Modeling the hierarchical structure of learning Peter W. Hill; 6. A study of longitudinal causal models comparing gain score analysis with structural equation approaches Leslie Hendrickson and Barnie Jones; 7. Some structural equation models of sibling resemblance in educational attainment and occupational status Robert M. Hauser and Peter A. Mossel; 8. Applications of structural equation modeling to longitudinal educational data Russell Ecob; 9. The robustness of maximum likelihood estimation in structural equation models Anne Boomsma; 10. An inquiry into the effects of outliers on estimates of a structural equation model of basic skills assessment Joan K. Gallini and Jim F. Casteel; 11. Testing structural equation models W. E. Saris, J. Den Ronden and A. Satorra; 12. LISREL models for inequality constraints in factor and regression analysis Henk Kelderman; 13. Issues and problems in the application of structural equation models Peter Cuttance; Appendix; Glossary; Index.
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