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Event History Analysis (Statistical theory and Application in the Social Sciences)
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Product Details
Author:
Hans-Peter Blossfeld, Alfred Hamerle, Karl Ulrich Mayer
Format:
Paperback
Pages:
298
Publisher:
Taylor & Francis (July 21, 2016)
Language:
English
ISBN-13:
9781138969179
Weight:
19.5oz
Dimensions:
6" x 9"
File:
TAYLORFRANCIS-TayFran_260618045536727-20260618.xml
Folder:
TAYLORFRANCIS
List Price:
$45.99
Case Pack:
1
As low as:
$43.69
Publisher Identifier:
P-CRC
Discount Code:
H
Audience:
Professional and scholarly
Country of Origin:
United States
Pub Discount:
30
Imprint:
Psychology Press
Overview
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.
