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Dynamic Analysis in the Social Sciences

Author:
Emilio J. Castilla
Publisher: Emerald Publishing
Copyright: 2007
ISBN-13: 978-0-12-088485-8
Pages: 300; hardcover
Price: $84.50

Comment from the Stata technical group

Dynamic Analysis in the Social Sciences, by Emilio Castilla, introduces social-science students to longitudinal data analysis, cross-sectional time-series analysis, and survival analysis. Castilla assumes a minimal level of statistical knowledge and covers a broad range of topics aimed at familiarizing readers with a variety of methods. Many of the examples in the book use Stata.

After discussing the different types of data encountered by social scientists, Castilla gives a useful taxonomy of methods by data structure. A chapter on longitudinal data introduces the reader to methods for panel data, in which many individuals are observed for a few time periods, and methods for cross-sectional time series, in which some (a few or many) individuals are observed for many time periods. A chapter on event history introduces survival analysis.

A chapter on designing a research study and a chapter with applications show students how to design and implement social-science studies. Castilla is very instructive in his careful discussions about formulating hypotheses and interpreting results. The book's annotated bibliography is a good resource for finding in-depth treatments of the covered topics.


Table of contents

List of Tables
List of Figures and Graphs
Preface
Acknowledgments
Author Biography
Chapter 1: Longitudinal Data
1. Some Basic Concepts and Terminology
1.1 Main Types of Variables
1.2 Univariate and Bivariate Statistics
1.3 First Example of a Longitudinal Data Set
1.4 Reading a Data Set into SPSS or Stata
2. Longitudinal Data
2.1 Types of Longitudinal Variables
3. Causes and Causal Relationships
4. Longitudinal Analysis: Definitions and Types
4.1 Why Longitudinal Analysis?
4.2 Longitudinal Analysis of Qualitative Variables
4.3 Longitudinal Analysis of Quantitative Variables
5. Organization and Characteristics of the Book
6. What You Need to Know
Chapter 2: Longitudinal Analysis of Quantitative Variables
1. A Practical Example
2. Multiple Regression Model with Panel Data
3. Limitations of the OLS Regression Model with Panel Data
4. Models for the Analyses of Panel Data
5. Constant Coefficients Model
5.1 Heteroskedastic Models
5.2 Autoregressive Models
5.3 Models with the Lagged Dependent Variable
5.4 Models with Instrumental Variables
5.5 The Basic ARIMA Models
6. Fixed Effects Model
7. Random Effects Model
8. Structural Equations Modeling
9. There Is Still More
Chapter 3: Event History Analysis
1. Event History Data
2. A Practical Example
3. Basic Methodology for the Analysis of Events
4. Dynamic Methodology for the Analysis of Events
5. Fundamentals of EHA: The Hazard Rate
6. Exploratory Analysis of Events
6.1 Life Tables
6.2 The Kaplan–Meier Estimators
6.3 Comparing Two Groups over Time
7. Explanatory or Multivariate Analysis of Events
7.1 Proportional Hazard Rate Models
7.2 Estimation of the Proportional Hazard Rate Model
7.3 Accelerated Failure Time Models
7.4 Choosing among Different Proportional Models
7.5 Testing the Proportional Hazard Rates Assumption
7.6 Non-Proportional Hazard Rate Models
7.7 Piecewise Exponential Models
8. EHA and Some Statistical Software Programs
9. An Example
10. More About EHA
Chapter 4: Designing a Study with Longitudinal Data
1. Writing a Research Paper: The Different Elements
2. The Introduction
3. Theory and Hypotheses
4. Longitudinal Data
5. Methodology for Data Analysis
6. Results
7. Discussion of Results
8. Conclusion
9. Bibliography and References
10. Abstract of a Study
11. Final Recommendations for Writing a Research Paper
12. Preparing a Research Paper for Publication
Chapter 5: Two Applications of Longitudinal Analysis
1. Social Networks and Employee Performance (Paper 1)
1.1 Introduction
1.2 Hypotheses
1.3 Research Setting
1.4 Methods
1.5 Results
1.6 Discussion and Conclusion
Acknowledgments
References
2. Institutional Aspects of National Science Activity (Paper 2)
2.1 Introduction
2.2 The International Council of Scientific Unions
2.3 Hypotheses
2.4 Description of Data
2.5 Exploratory Analysis
2.6 Multivariate Methods
2.7 Discussion of Results
2.8 Conclusion
Acknowledgments
References
List of References (with comments)
Basic Data Analysis
Longitudinal Data
Applications of Basic Data Analysis in the Social Sciences
Longitudinal Analyses of Quantitative Variables
Applications of Longitudinal Analysis of Quantitative Variables
Event History Analysis
Applications of Event History Analysis
On Writing and Publishing Research Papers
To Learn About Statistical Software Programs
Other Chapter References
Index
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