## Structural Equation Modeling: Concepts, Issues, and ApplicationsThis book includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. It targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences. Contents: - Basic Concepts - Model Specification - Estimates and Tests - Nonnormal Variables - Evaluating Model Fit - Statistical Power - Objectivity and Reasoning - Exploring the EQS and LISREL Strategies - Writing about Structural Equation Models - Latent Variable Models - Sex-Race Differences in Social Support and Depression in Older Low-Income Adults - Modeling the Relation of Personality Variables to Symptom Complaints - Predictors of Change in Antisocial Behavior During Elementary School for Boys. |

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### Contents

The Structural Equation Modeling Approach | 1 |

Procedures Strategies | 16 |

Estimates and Tests in Structural Equation Modeling | 37 |

Summary and Recommendations | 54 |

Evaluating Model Fit | 76 |

Reevaluation of Fit Indexes as Alternative Measures | 89 |

Statistical Power in Structural Equation Modeling | 100 |

PowerBased Model Evaluation | 107 |

Summary and Implications | 196 |

SexRace Differences in Social Support and Depression | 199 |

Method | 205 |

The GroupSensitive Model | 211 |

Modeling the Relation of Personality Variables to Symptom | 217 |

Method | 223 |

Predictors of Change in Antisocial Behavior During | 236 |

Results | 243 |

Conclusion | 114 |

Objectivity and Reasoning in Science and Structural | 118 |

One Application of Structural Equation Modeling From | 138 |

Writing About Structural Equation Models | 158 |

Latent Variable Models of MultitraitMultimethod Data | 177 |

Direct Product Models | 187 |

Discussion | 249 |

254 | |

Author Index | 272 |

278 | |

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### Common terms and phrases

alternative approach assessed associated assumptions asymptotic Bollen causal CDP model CFA models Chapter constraints construct convergent validity correlations covariance matrix degrees of freedom dependent variable depression discrepancy function endogenous estimation methods evaluation factor analysis factor loadings factor model free parameters function goodness-of-fit groups homophily hypotheses independent indicators Joreskog Kaplan kurtosis latent variables linear LISREL logical positivism MacCallum Marsh measured variables method effects method factors ML and GLS model fit model modification Mulaik multiple multivariate normality negative affectivity neuroticism noncentrality nonnormal normal theory null hypothesis observed data observed variables parameter estimates path diagram regression represent sample covariance matrix sample size sample sizes Satorra SCALED second-order factor skewness social support solution Sorbom standard errors structural equation modeling Study symptom complaints test statistic tion typically unique values variance Wald test x2 distribution x2 statistic x2 test zero