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LATENT CURVE MODELS: A STRUCTURAL EQUATION PERSPECTIVE本征曲线模型:结构方程途径

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LATENT CURVE MODELS: A STRUCTURAL EQUATION PERSPECTIVE本征曲线模型:结构方程途径

最 低 价:¥862.20

定 价:¥958.00

作 者:Kenneth A. Bollen,Patrick J. Curran 著

出 版 社:吉林长白山

出版时间:2005-12-1

I S B N:9780471455929

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内容简介

This volume represents a comprehensive treatment of a model sometimes referred to as latent curve or growth curve models. Latent Curve Models analyzes LTMs from the perspective of structural equation modeling (SEM) with latent variables. Although the authors discuss simple regression-based procedures that are helpful in the early stages of LTM, most of the presentation will use SEMs as a driving tool throughout the text.
  作者简介:
  KENNETH A. BOLLEN, PhD, is Henry Rudolph Immerwahr Distinguished Professor of Sociology, Director of the Odum Institute for Research in Social Science, and an Adjunct Professor of Statistics at The University of North Carolina at Chapel Hill. He is the author of two books, including Structural Equations with Latent Variables (Wiley), and more than 100 scholarly papers.
  PATRICK J. CURRAN, PhD, is Associate Professor of Psychology in the L. L. Thurstone Psychometric Laboratory at The University of North Carolina at Chapel Hill. He has made contributions to the development and application of new quantitative methodologies in the social sciences through his integrated program of research, writing, and teaching.

作者简介

目录

Preface
1 Introduction
 1.1 Conceptualization and Analysis of Trajectorie
  1.1.1 Trajectories of Crime Rates
  1.1.2 Data Requirements
  1.1.3 Summary
 1.2 Three Initial Questions About Trajectories
  1.2.1 Question 1: What Is the Trajectory for the Entire Group?
  1.2.2 Question 2: Do We Need Distinct Trajectories for Each Case?
  1.2.3 Question 3: If Distinct Trajectories Are Needed, Can We Identify Variables to Predict These Individual Trajectories?
  1.2.4 Summary
 1.3 Brief History of Latent Curve Models,
  1.3.1 Early Develpments: The Nineteenth Century,
  1.3.2 Fitting Group Trajectories: 1900-1937
  1.3.3 Fitting Individual and Group Trajectories:1938-1950s
  1.3.4 Trajectory Modeling with Latent Variables:1950s-1984
  1.3.5 Current Latent Curve Modeling: 1984-present
  1.3.6 Summary
1.4 Organization of the Remainder of the Book
2 Unconditional Latent Curve Model
 2.1 Repeated Measures
 2.2 General Model and Assumptions
 2.3 Identification
 2.4 Case-By-Case Approach
  2.4.1 Assessing Model Fit
  2.4.2 Limitations of Case-by-Case Approach
 2.5 Structural Equation Model Approach
  2.5.1 Matrix Expression of the Latent Curve Model
  2.5.2 Maximum Likelihood Estimation
  2.5.3 Empirical Example
  2.5.4 Assessing Model Fit
  2.5.5 Components of Fit
 2.6 Alternative Approaches to the SEM
 2.7 Conclusions
 Appendix 2A: Test Statistics, Nonnormality, and Statistical Power
3 Missing Data and Alternative Metrics of Time
 3.1 Missing Data
  3.1.1 Types of Missing Data
  3.1.2 Treatment of Missing Data
  3.1.3 Empirical Example
  3.1.4 Summary
 3.2 Missing Data and Alternative Metrics of Time
  3.2.1 Numerical Measure of Time
  3.2.2 When Wave of Assessment and Alternative Metrics of Time Are Equivalent
  3.2.3 When Wave of Assessment and Alternative M~trics of Time Are Different
  3.2.4 Reorganizing Data as a runction of Alternatiye Metrics of Time
  3.2.5 Individually Varying Values of Time,
  3.2.6 Summary
  3.2.7 Empirical Example: Reading Achievement,
 3.3 Conclusions
4 Nonlinear Trajectories and the Coding of Time
 4.1 Modeling Nonlinear Functions of Time
  4.1.1 Polynomial Trajectories: Quadratic Trajectory Model
  ……
5 Conditional Latent Curve Models
6 The Analysis of Groups
7 Multivariate Latent Curve Models
8 Extensions of Latent Curve Models
References
Author Index
Subject Index

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