Event History Modeling: A Guide for Social Scientists by Box-Steffensmeier: Used

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Specificaties

Objectstaat
Goed: Een boek dat is gelezen, maar zich in goede staat bevindt. De kaft is zeer minimaal beschadigd ...
Book Title
Event History Modeling: A Guide for Social Scientists
Publication Date
2004-04-05
ISBN
9780521837675

Over dit product

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
0521837677
ISBN-13
9780521837675
eBay Product ID (ePID)
5975542

Product Key Features

Number of Pages
234 Pages
Publication Name
Event History Modeling : a Guide for Social Scientists
Language
English
Subject
Methodology, General
Publication Year
2004
Type
Textbook
Subject Area
Political Science, Social Science
Author
Janet M. Box-Steffensmeier, Bradford S. Jones
Series
Analytical Methods for Social Research Ser.
Format
Hardcover

Dimensions

Item Height
0.7 in
Item Weight
18.4 Oz
Item Length
9 in
Item Width
6 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2003-056923
Dewey Edition
22
Reviews
"Box-Steffensmeier and Jones have written a highly accessible and incredibly thoughtful introduction to survival analysis for the social scientist. I find Event History Modeling to be well suited for adoption both as a graduate and self study test. Highly recommended." --Tze Kwang Teo, University of Illinois at Urbana-Champaign, The Political Methodologist
Illustrated
Yes
Dewey Decimal
001.4/32
Table Of Content
List of figures; List of tables; Preface; 1. Event history and political analysis; 2. The logic of event history analysis; 3. Parametric models for single-spell duration data; 4. The Cox Proportional Hazards model; 5. Models for discrete data; 6. Issues in model selection; 7. Inclusion of time-varying covariates; 8. Diagnostic methods for the event history model; 9. Some modeling strategies for unobserved heterogeneity; 10. Models for multiple events; 11. Political analysis and event history; Appendix: software for event history analysis; References; Index.
Synopsis
Here is an accessible, up-to-date guide to event history analysis for researchers and advanced students in the social sciences. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Recent and critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods., Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students in the social sciences. The substantive focus of many social science research problems leads directly to the consideration of duration models, and many problems would be better analyzed by using these longitudinal methods to take into account not only whether the event happened, but when. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods., This 2004 book provides a guide to event history analysis for researchers and advanced students in the social sciences. The authors explain the foundational principles of event-history analysis, and analyse numerous examples. They also discuss common problems encountered with time-to-event data, along with suggestions for implementing duration modeling methods.
LC Classification Number
H61 .B6366 2004

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