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Event History Analysis: Applied Social Research Methods, cartea 28

Autor Kazuo Yamaguchi
en Limba Engleză Paperback – 25 sep 1991
This book provides a systematic introduction to models, methods and applications of event history analysis. Yamaguchi emphasizes 'hands on' information, including the use and misuse of samples, models and covariates in applications, the structural arrangement of input data, the specification of various models in such computer programs as SAS-LOGIST and SPSSX-LOGLINEAR, and the interpretation of parameters estimated from models. The book also explores such significant topics as missing data, hazard rate, Cox's partial likelihood model, survivor function, and discrete-time logit models.
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Specificații

ISBN-13: 9780803933248
ISBN-10: 080393324X
Pagini: 182
Dimensiuni: 165 x 225 x 12 mm
Greutate: 0.26 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Seria Applied Social Research Methods

Locul publicării:Thousand Oaks, United States

Cuprins

Introduction
What is Event History Analysis?
Discrete Time-Logit Model
The Analysis of One-Way Transition
Discrete Time-Logit Model
The Analysis of Two-Way Transitions
Log-Rate Models for Piecewise Constant Rates
Continuous-Time Models with Cox's Method
Proportional Hazards Models, Non-Proportional Hazards Models, and Stratified Models
Continuous-Time Models with Cox's Method
Use of Time-Dependent Covariates and Related Issues
Final Remarks Before Getting One's Own Research Started

Notă biografică

Professor Yamaguchi is interested in statistical models for social data and mathematical models for social phenomena, the life course, rational choice, exchange networks, stratification and mobility, demography for family and employment, process of drug use progression. His current research focuses on models of exchange networks and women¿s occupational careers in Japanese society.

Descriere

This book provides a systematic introduction to models, methods and applications of event history analysis. Yamaguchi emphasizes 'hands on' information, including the use and misuse of samples, models and covariates in applications, the structural arrangement of input data, the specification of various models in such computer programs as SAS-LOGIST and SPSSX-LOGLINEAR, and the interpretation of parameters estimated from models. The book also explores such significant topics as missing data, hazard rate, Cox's partial likelihood model, survivor function, and discrete-time logit models.