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Event History Modeling: A Guide for Social Scientists Paperback - 2004
by Janet M. Box-Steffensmeier; Bradford S. Jones
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- Title Event History Modeling: A Guide for Social Scientists
- Author Janet M. Box-Steffensmeier; Bradford S. Jones
- Binding Paperback
- Edition [ Edition: Repri
- Pages 234
- Volumes 1
- Language ENG
- Publisher Cambridge University Press
- Date 2004-03-29
- Illustrated Yes
- ISBN 9780521546737 / 0521546737
- Weight 0.8 lbs (0.36 kg)
- Dimensions 9 x 5.9 x 0.3 in (22.86 x 14.99 x 0.76 cm)
- Library of Congress subjects History - Methodology, Social sciences - Methodology
- Library of Congress Catalog Number 2003056923
- Dewey Decimal Code 001.432
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Event History Modeling: A Guide for Social Scientists (Analytical Methods for Social Research)
by Box-Steffensmeier, Janet M., Jones, Bradford S.
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Event History Modeling: A Guide for Social Scientists (Analytical Methods for Social Research)
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Event History Modeling: A Guide for Social Scientists
by Janet M. Box-Steffensmeier/ Bradford S. Jones
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Paperback / softback. New. 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.
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Event History Modeling: A Guide for Social Scientists (Analytical Methods for Social Research) : by Janet M. Box-Steffensmeier and Bradford S. Jones
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ISBN: 9780521546737Cambridge University Press | 01 April 2004
Paperback | 234 pages
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.
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