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Record Nr. |
UNINA9910457685003321 |
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Autore |
Box-Steffensmeier Janet M. <1965-> |
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Titolo |
Event history modeling : a guide for social scientists / / Janet M. Box-Steffensmeier, Bradford S. Jones [[electronic resource]] |
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Pubbl/distr/stampa |
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Cambridge : , : Cambridge University Press, , 2004 |
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ISBN |
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1-107-15042-6 |
1-280-47751-2 |
0-511-79087-2 |
0-511-19543-5 |
0-511-19609-1 |
0-511-19405-6 |
0-511-31441-8 |
0-511-19479-X |
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Descrizione fisica |
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1 online resource (xiii, 218 pages) : digital, PDF file(s) |
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Collana |
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Analytical methods for social research |
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Disciplina |
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Soggetti |
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Event history analysis - Computer simulation |
Social sciences - Methodology |
History - Methodology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
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Nota di bibliografia |
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Includes bibliographical references (p. 201-211) and index. |
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Nota di contenuto |
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Cover; Half-title; Title; Copyright; Dedication; Contents; Figures; Tables; Preface; CHAPTER 1 Event History and Social Science; CHAPTER 2 The Logic of Event History Analysis; CHAPTER 3 Parametric Models for Single-Spell Duration Data; CHAPTER 4 The Cox Proportional Hazards Model; CHAPTER 5 Models for Discrete Data; CHAPTER 6 Issues in Model Selection; CHAPTER 7 Inclusion of Time-Varying Covariates; CHAPTER 8 Diagnostic Methods for the Event History Model; CHAPTER 9 Some Modeling Strategies for Unobserved Heterogeneity; CHAPTER 10 Models for Multiple Events |
CHAPTER 11 The Social Sciences and Event HistoryAppendix Software for Event History Analysis; References; Index |
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Sommario/riassunto |
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Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students |
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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. |
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