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Social Dynamics Models and Methods
- 1st Edition - August 28, 1984
- Editor: Nancy Brandon Tuma
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 4 3 3 3 7 8 - 9
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 1 5 6 9 0 - 5
Social Dynamics: Models and Methods focuses on sociological methodology and on the practice of sociological research. This book is organized into three parts encompassing 16… Read more
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Request a sales quoteSocial Dynamics: Models and Methods focuses on sociological methodology and on the practice of sociological research. This book is organized into three parts encompassing 16 chapters that deal with the basic principles of social dynamics. The first part of this book considers the development of models and methods for causal analysis of the actual time paths of change in attributes of individual and social systems. This part also discusses the applications in which the use of dynamic models and methods seems to have enhanced the capacity to formulate and test sociological arguments. These models and methods are useful for answering questions about the detailed structure of social change processes. The second part explores the formulation of the continuous-time models of change in both quantitative and qualitative outcomes and the development of suitable methods for estimating these models from the kinds of data commonly available to sociologists. The third part describes a stochastic framework for analyzing both qualitative and quantitative outcome of social changes. This part also discusses the sociologists' perspective on the empirical study of social change processes. This text will be of great value to sociologists and sociological researchers.
Preface
Acknowledgments
Part I Introduction
1 Why Dynamic Analysis?
1.1 Static Analysis for Studying Change
1.2 Dynamic Analysis for Studying Static Relationships
1.3 Other Obstacles to Dynamic Analysis
1.4 Conclusions
2 Varieties of Temporal Analysis: Overview and Critique
2.1 Observation Plans
2.2 Panel Analysis of Qualitative Outcomes
2.3 Event-History Analysis
2.4 Panel Analysis of Quantitative Outcomes
2.5 Time-Series Analysis
2.6 Conclusions
Part II Qualitative Outcomes
3 Fundamentals of Event-History Analysis
3.1 Event-History Data
3.2 Terms for Populations of Event Histories
3.3 Conclusions
4 Models of Change in Qualitative Variables
4.1 Reasons for Continuous-Time Stochastic Models
4.2 Models of Event Histories
4.3 Implications of Semi-Markov Models
4.4 Particular Models
4.5 Conclusions
5 Estimation Using Censored Event Histories
5.1 The Censoring Problem
5.2 Maximum-Likelihood Estimation
5.3 ML Estimation of Right-Censored Event Histories
5.4 ML Estimation of Left-Censored Event Histories
5.5 ML Estimators for a Single Constant Rate
5.6 Two Pseudo-ML Estimators
5.7 A Moment Estimator
5.8 Monte Carlo Results on Effects of Censoring
5.9 Measurement Error in Dates
5.10 Monte Carlo Results on Measurement Error
5.11 Markov Models with Multiple Outcomes
5.12 Conclusions
6 Models for Heterogeneous Populations
6.1 Parameterizing Observed Heterogeneity
6.2 An Example: NIT Effects on Marital Stability
6.3 Incorporating Unobserved Heterogeneity
6.4 An Example: Unobserved Heterogeneity in Job-Shift Rates
6.5 Misspecification of the Disturbance’s Distribution
6.6 Conclusions
7 Time Dependence: Parametric Approaches
7.1 Sources of Time Dependence
7.2 Periodic Shifts in Parameters and Causal Variables
7.3 Linearly Changing Causal Variables
7.4 Time as a Proxy for Unobserved Change Processes
7.5 Conclusions
8 Time Dependence: A Partially Parametric Approach
8.1 Proportional Rates
8.2 Partial Likelihood
8.3 Monte Carlo Study of PL and ML Estimators
8.4 PL Estimation of a Hazard Function Illustrated
8.5 Handling of Ties
8.6 Intermittently Measured Explanatory Variables
8.7 Estimating the Nuisance and Survivor Functions
8.8 Sources of Variation in the Nuisance Function
8.9 Multiple Outcomes
8.10 PL Estimation of Transition Rates Illustrated
8.11 Repeatable Events
8.12 Conclusions
9 Systems of Qualitative Variables
9.1 Modeling Strategies
9.2 An Example: Marital Status and Employment Statuses
9.3 Consequences of Ignoring Interdependence
9.4 Conclusions
10 A Comparison of Approaches
10.1 Cross-Sectional Analysis
10.2 Event-Count and Event-Sequence Analysis
10.3 Panel Analysis
10.4 An Example: Formal Political Structure
10.5 How Well Do These Models Fit?
10.6 Conclusions
Part III Quantitative Outcomes
11 Linear Deterministic Models
11.1 Linear Models for Rates of Change
11.2 Time Paths of Changes: Integral Equations
11.3 An Example: Organizational Growth and Decline
11.4 Linear Systems
11.5 Integral Equations for Linear Systems
11.6 Qualitative Stability
11.7 Organizational Growth and Decline Reconsidered
11.8 Conclusions
Appendix
12 Linear Stochastic Models
12.1 Need for Stochastic Models
12.2 Stochastic Differential Equations
12.3 Complicating the Noise Process
12.4 Diffusion Processes
12.5 Boundary Behavior
12.6 Systems of Equations
12.7 Conclusions
13 Estimation of Linear Models
13.1 Time-Series versus Panel Data
13.2 Two Ways to Estimate a Dynamic Model
13.3 Scalar Models
13.4 Autocorrelation of Disturbances
13.5 Pooled Cross-Section and Time-Series Estimators
13.6 Monte Carlo Studies of Pooled Estimators
13.7 Measurement Error
13.8 Unequally Spaced Observations
13.9 Linear Systems
13.10 Conclusions
14 Deterministic Nonlinear Models
14.1 Scalar Models
14.2 Models of Systems
14.3 Competition Models
14.4 Exact Discrete Approximations
14.5 An Example: National Expansion of Education
14.6 Qualitative Stability
14.7 Cyclic Behavior: Predator-Prey Interactions
14.8 Conclusions
15 Stochastic Nonlinear Models
15.1 Stochastic Integrals: The Nonlinear Case
15.2 Geometric Brownian Motion
15.3 The Itŏ Transformation Formula
15.4 Conclusions
16 Coupled Qualitative and Quantitative Processes
16.1 Quality and Quantity
16.2 Approaches
16.3 Conclusions
References
Author Index
Subject Index
- No. of pages: 302
- Language: English
- Edition: 1
- Published: August 28, 1984
- Imprint: Academic Press
- Paperback ISBN: 9780124333789
- eBook ISBN: 9780323156905