Event History Analysis
Statistical theory and Application in the Social Sciences
1st Edition
Published on 24. February 2014
298 pages
978-1-317-78572-9 (ISBN)
Description
Serving as both a student textbook and a professional reference/handbook, this volume explores the statistical methods of examining time intervals between successive state transitions or events. Examples include: survival rates of patients in medical studies, unemployment periods in economic studies, or the period of time it takes a criminal to break the law after his release in a criminological study. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to the specific questions of data organization, to the concrete application of available program packages and the interpretation of the obtained results.
Event History Analysis:
* makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples
* presents the unabbreviated close relationship underlying statistical theory
* details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation
* discusses specific problems of multi-state and multi-episode models
* introduces time-varying covariates and the question of unobserved population heterogeneity
* demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.
Event History Analysis:
* makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples
* presents the unabbreviated close relationship underlying statistical theory
* details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation
* discusses specific problems of multi-state and multi-episode models
* introduces time-varying covariates and the question of unobserved population heterogeneity
* demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.
Reviews / Votes
"Its greatest usefulness is probably in a course for graduate students of applied statistics....the classical standard packages remain an important tool for many analysts, who are bound to find this text very helpful as a work of reference when they set up their computations."-European Sociological Review
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
File size
5,66 MB
ISBN-13
978-1-317-78572-9 (9781317785729)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Hans-Peter Blossfeld | Alfred Hamerle | Karl Ulrich Mayer
Event History Analysis
Statistical theory and Application in the Social Sciences
Book
07/2016
1st Edition
Psychology Press Ltd
€59.60
Shipment within 10-20 days
Hans-Peter Blossfeld | Alfred Hamerle | Karl Ulrich Mayer
Event History Analysis
Statistical theory and Application in the Social Sciences
Book
11/1988
1st Edition
Psychology Press
€133.69
Shipment within 10-20 days
Persons
Hans-Peter Blossfeld, Alfred Hamerle, Karl Ulrich Mayer
Content
Contents: Foreword. Aim and Structure of the Book. Domains and Rationale for the Application of Event History Analysis. The Statistical Theory of Event History Analysis. Data Organization and Descriptive Methods. Semi-Parametric Regression Models: The Cox Proportional Hazards Model. Parametric Regression Models. Appendices: List of Variable Names Used in Examples. Listing of the FORTRAN Program PR3FUN Written by Trond Petersen. Listing of the FORTRAN Program for Episode Splitting Given Discrete Time-Dependent Covariates. Listing of the FORTRAN Program for Episode Splitting Given Continuous Time-Dependent Covariates. Listing of the GLIM Macros to Estimate the Weibull and Log-Logistic Models of Roger and Peacock.
