Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction.
Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of job and career mobility, which is one of the approaches taken by sociologists in research on the labor market. Other chapters consider the characteristic trends and patterns from data on divorces. This book discusses as well the two approaches of stochastic modeling of social processes, namely competing risk models and semi-Markov processes. The final chapter deals with the practical application of regression models of survival data.
This book is a valuable resource for social scientists and statisticians.
New Aspects of Stochastic Model Building in the Social Sciences
Multistate Demography and Event History Analysis
Interpreting Time Dependency in Career Processes
A Comparison of the "Sickle Function" with Alternative Stochastic Models of Divorce Rates
Semi-Markov and Competing Risks Models with Applications to Occupational Mobility
Stochastic Models for Market Structures
Markovian Transition Rates Models of Macro Social Change
Analysis of Event Histories with Generalized Linear Models
Survival Analysis in Heterogeneous Populations—Statistical Models and Concepts
- No. of pages:
- © Academic Press 1984
- 28th January 1984
- Academic Press
- eBook ISBN: