Statistical Methods in Longitudinal Research : Time Series and Categorical Longitudinal Data.

Bibliographic Details
Main Author:	Von Eye, Alexander
Corporate Author:	EBSCOhost
Format:	eBook
Language:	English
Published:	Saint Louis : Elsevier Science, 1990.
Series:	Statistical modeling and decision science.
Subjects:	Social sciences > Research > Statistical methods. MATHEMATICS > Applied. MATHEMATICS > Probability & Statistics > General. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Front Cover; Time Series and Categorical Longitudinal Data; Copyright Page; Contents of Volume II; Contents of Volume I; Contributors; Preface; PART III: Analysis of Time Series; Chapter 7. Analyzing Event Histories; Abstract; 1 Introduction; 2. Basic Concepts; 3. Dependence of the Hazard Rate on Covariates; 4. Comparison to Standard Regression Models; 5. Repeated Events; 6. Multistate Processes; 7. Unobserved Heterogeneity; 8. Theoretical Models Generating Event Histories; 9. Empirical Analysis; 10. Concluding Remarks; Appendix A. Proof of the Survivor Function in Equation (13).
Appendix B. Computer Programs for Estimating Hazard Rate ModelsReferences; Chapter 8. Linear and Nonlinear Curve Fitting; Abstract; 1. Models for Growth; 2. Incorporating Information from the Population; 3. Nonlinear Prediction; 4. Conclusions; References; Chapter 9. Spectral Analysis of Psychological Data; Abstract; 1. Time-Series Statistics; 2. Spectral Analysis: An Intuitive Description; 3. Assumptions of Spectral Analysis; 5. Bivariate Spectral Analysis; 4. Spectral Analysis of Psychological Data: A Worked Example; 6. Computer Programs for Spectral Analysis; References.
Chapter 10. Univariate and Multivariate Time-Series Models: The Analysis of Intraindividual Variability and Intraindividual RelationshipsAbstract; 1. Introduction; 2. Basic Terms; 3. Univariate ARIMA Models; 4. Conducting Time-Series AnalysisIt; 5. Multivariate ARIMA Model; 6. Summary and Discussion; References; Chapter 11. Descriptive and Associative Developmental Models; Abstract; 1. Introduction; 2. A Univariate Longitudinal Model; 3. A Multivariate Longitudinal Model; 4. Descriptive Developmental Models; 5. Associative Developmental Models; 6. A Simple Example; 7. An Associative Model.
2. Procedural Outline of Latent Class Analysis3. Example: Conservation of Weight; 4. Hierarchical Models; 5. Models for Panel Data; 6. Multiple-Group Models; 7. Relationship of Latent Class Analysis to Other Methods of Analysis; 8. Do-It-Yourself Estimation; 9. Summary; References; Chapter 14. Deterministic Developmental Hypotheses, Probabilistic Rules of Manifestation, and the Analysis of Finite Mixture Distributions; Abstract; 1. Testing Deterministic Developmental Theories by Means of Finite Mixture Distribution Analysis; 2. The General Finite Mixture Model.