Leslie A. Hayduk is professor in the Department of Sociology at the University of Alberta. He is the author of Structural Equation Modeling with LISREL, also available from Johns Hopkins.

• PrefaceAcknowledgmentsChapter 1. Getting Started1.1 Means, variances, and covariance1.2 Thinking about covariances, variances, and means1.3 Expectations and equations1.4 Structural equation modelsChapter 2. Traditional Basics2.1 Fitting a line into a scatterplot2.2 Regression in the context of Chapter 12.3 Multiple regression2.4 Colinearity2.5 Interaction2.6 Nonlinearity Chapter 3. The New Basics3.1 A touch of matrix algebra3.2 Derivatives in a few easy pagesChapter 4. In the Beginning4.1 A new way of thinking. latent versus measured variables in causal modes4.2 LISREL is Greek to me!4.3 A real model. smoking behavior and antismoking acts4.4 A model implies a sigma ()4.5 Scaling and reliability4.6 Restrictions on model specificationChapter 5. Estimating Structural Coefficients with Maximum Likelihood Estimation5.1 Maximum likelihood estimation5.2 Making approximate S5.3 Identification and colinearity5.4 On simplifying models5.5 In closingChapter 6. Hitting Paydirt6.1 Chi-square6.2 Residuals6.3 Fitting better than the competition6.4 Significance of structural coefficients6.5 Partial derivatives and their uses6.6 Standardized solutionsChapter 7. Becoming a LISRELITE. Some Tricks of the Trade and Learning to Play7.1 Four simple replacements7.2 Moving into and rethinking the distinction between exogenous/endogenous7.3 Multiple indicators7.4 Nonlinearity among the concepts7.5 Interaction among the conceptsChapter 8. Interpreting It All8.1 The Basics8.2 General matrix formulas8.3 Two extensions of effect decompositions8.4 On developing equivalent models (effect recomposition)8.5 Interpreting the smoking model with an inserted loop8.6 SummaryChapter 9. More and Better9.1 Stacked models for multiple groups9.2 Modeling meansChapter 10. Odds and Endings10.1 Old Beta10.2 LISREL in SPSSX and pairwise matrices10.3Some data-related issues 10.4 Locating what is wrong in a program10.5 Alternative estimation strategies10.6 A guide to the literature10.7 The end AppendicesAppendix A. Summation NotationAppendix B. LISREL Output for the Smoking ModelAppendix C. LISREL Output with Multiple IndicatorsAppendix D. The Moment Matrix Fit FunctionBibliographyIndex

Hayduk is equally at ease explaining the simplest and most advanced applications of the program... Hayduk has written more than just a solid text for use in advanced graduate courses on statistical modeling. Those with a firm mathematical background who wish to learn about the approach, or those who know a little about the program and want to know more, will find this an excellent reference. American Journal of Sociology This is a fine book for providing persons who have a basic knowledge of regression and matrix algebra with a detailed understanding of LISREL. It is strong on explanation, on clarity, and on breadth of coverage. Contemporary Psychology

Leslie A. Hayduk is professor in the Department of Sociology at the University of Alberta. He is the author of Structural Equation Modeling with LISREL, also available from Johns Hopkins.

• PrefaceAcknowledgmentsChapter 1. Getting Started1.1 Means, variances, and covariance1.2 Thinking about covariances, variances, and means1.3 Expectations and equations1.4 Structural equation modelsChapter 2. Traditional Basics2.1 Fitting a line into a scatterplot2.2 Regression in the context of Chapter 12.3 Multiple regression2.4 Colinearity2.5 Interaction2.6 Nonlinearity Chapter 3. The New Basics3.1 A touch of matrix algebra3.2 Derivatives in a few easy pagesChapter 4. In the Beginning4.1 A new way of thinking. latent versus measured variables in causal modes4.2 LISREL is Greek to me!4.3 A real model. smoking behavior and antismoking acts4.4 A model implies a sigma ()4.5 Scaling and reliability4.6 Restrictions on model specificationChapter 5. Estimating Structural Coefficients with Maximum Likelihood Estimation5.1 Maximum likelihood estimation5.2 Making approximate S5.3 Identification and colinearity5.4 On simplifying models5.5 In closingChapter 6. Hitting Paydirt6.1 Chi-square6.2 Residuals6.3 Fitting better than the competition6.4 Significance of structural coefficients6.5 Partial derivatives and their uses6.6 Standardized solutionsChapter 7. Becoming a LISRELITE. Some Tricks of the Trade and Learning to Play7.1 Four simple replacements7.2 Moving into and rethinking the distinction between exogenous/endogenous7.3 Multiple indicators7.4 Nonlinearity among the concepts7.5 Interaction among the conceptsChapter 8. Interpreting It All8.1 The Basics8.2 General matrix formulas8.3 Two extensions of effect decompositions8.4 On developing equivalent models (effect recomposition)8.5 Interpreting the smoking model with an inserted loop8.6 SummaryChapter 9. More and Better9.1 Stacked models for multiple groups9.2 Modeling meansChapter 10. Odds and Endings10.1 Old Beta10.2 LISREL in SPSSX and pairwise matrices10.3Some data-related issues 10.4 Locating what is wrong in a program10.5 Alternative estimation strategies10.6 A guide to the literature10.7 The end AppendicesAppendix A. Summation NotationAppendix B. LISREL Output for the Smoking ModelAppendix C. LISREL Output with Multiple IndicatorsAppendix D. The Moment Matrix Fit FunctionBibliographyIndex

Hayduk is equally at ease explaining the simplest and most advanced applications of the program... Hayduk has written more than just a solid text for use in advanced graduate courses on statistical modeling. Those with a firm mathematical background who wish to learn about the approach, or those who know a little about the program and want to know more, will find this an excellent reference. American Journal of Sociology This is a fine book for providing persons who have a basic knowledge of regression and matrix algebra with a detailed understanding of LISREL. It is strong on explanation, on clarity, and on breadth of coverage. Contemporary Psychology

Leslie A. Hayduk is professor in the Department of Sociology at the University of Alberta. He is the author of Structural Equation Modeling with LISREL, also available from Johns Hopkins.

• PrefaceAcknowledgmentsChapter 1. Getting Started1.1 Means, variances, and covariance1.2 Thinking about covariances, variances, and means1.3 Expectations and equations1.4 Structural equation modelsChapter 2. Traditional Basics2.1 Fitting a line into a scatterplot2.2 Regression in the context of Chapter 12.3 Multiple regression2.4 Colinearity2.5 Interaction2.6 Nonlinearity Chapter 3. The New Basics3.1 A touch of matrix algebra3.2 Derivatives in a few easy pagesChapter 4. In the Beginning4.1 A new way of thinking. latent versus measured variables in causal modes4.2 LISREL is Greek to me!4.3 A real model. smoking behavior and antismoking acts4.4 A model implies a sigma ()4.5 Scaling and reliability4.6 Restrictions on model specificationChapter 5. Estimating Structural Coefficients with Maximum Likelihood Estimation5.1 Maximum likelihood estimation5.2 Making approximate S5.3 Identification and colinearity5.4 On simplifying models5.5 In closingChapter 6. Hitting Paydirt6.1 Chi-square6.2 Residuals6.3 Fitting better than the competition6.4 Significance of structural coefficients6.5 Partial derivatives and their uses6.6 Standardized solutionsChapter 7. Becoming a LISRELITE. Some Tricks of the Trade and Learning to Play7.1 Four simple replacements7.2 Moving into and rethinking the distinction between exogenous/endogenous7.3 Multiple indicators7.4 Nonlinearity among the concepts7.5 Interaction among the conceptsChapter 8. Interpreting It All8.1 The Basics8.2 General matrix formulas8.3 Two extensions of effect decompositions8.4 On developing equivalent models (effect recomposition)8.5 Interpreting the smoking model with an inserted loop8.6 SummaryChapter 9. More and Better9.1 Stacked models for multiple groups9.2 Modeling meansChapter 10. Odds and Endings10.1 Old Beta10.2 LISREL in SPSSX and pairwise matrices10.3Some data-related issues 10.4 Locating what is wrong in a program10.5 Alternative estimation strategies10.6 A guide to the literature10.7 The end AppendicesAppendix A. Summation NotationAppendix B. LISREL Output for the Smoking ModelAppendix C. LISREL Output with Multiple IndicatorsAppendix D. The Moment Matrix Fit FunctionBibliographyIndex

Hayduk is equally at ease explaining the simplest and most advanced applications of the program... Hayduk has written more than just a solid text for use in advanced graduate courses on statistical modeling. Those with a firm mathematical background who wish to learn about the approach, or those who know a little about the program and want to know more, will find this an excellent reference. American Journal of Sociology This is a fine book for providing persons who have a basic knowledge of regression and matrix algebra with a detailed understanding of LISREL. It is strong on explanation, on clarity, and on breadth of coverage. Contemporary Psychology