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A01=Alfred Hamerle
A01=Hans-Peter Blossfeld
A01=Karl Ulrich Mayer
advanced event data modeling
Author_Alfred Hamerle
Author_Hans-Peter Blossfeld
Author_Karl Ulrich Mayer
Category=JHBC
Covariate Vector
covariates
Cox Model
Cox regression
Cumulative Hazard Rate
data
Data Set
dependent
discrete time modeling
Duration Dependency
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
estimator
Event History Analysis
Event History Data
Exponential Model
FORTRAN statistical programs
GLHS
Gompertz Distribution
Gompertz Model
Hazard Rate
kaplan
Kaplan Meier Estimator
LFX
life
Life Table
Life Table Method
Log Likelihood
Log Logistic Model
meier
method
proportional hazards model
Regression Models
social science statistics
STANDARD VARIABLE COEFFICIENT ERROR
Survivor Function
table
time
Time Dependent Covariate
time-dependent covariates
Unobserved Heterogeneity
Unskilled Manual Occupation
Weibull Model

Product details

  • ISBN 9780805801262
  • Weight: 710g
  • Dimensions: 152 x 229mm
  • Publication Date: 01 Nov 1988
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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.

Hans-Peter Blossfeld, Alfred Hamerle, Karl Ulrich Mayer

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