You are here

Log-Linear Models for Event Histories
Share

Log-Linear Models for Event Histories



May 1997 | 360 pages | SAGE Publications, Inc
Event history analysisùa method for explaining why some people are more likely to experience a particular event, transition, or change than other peopleùhas been useful in the social sciences for studying the processes of social change. One of the main difficulties, however, in using this technique is that often information is (partially) missing on some of the relevant variables. Author Jeroen K. Vermunt presents a general approach to these missing data problems in event history analysis that is based on the similarities between log-linear, hazard, and event history models. The book begins with a discussion of log-linear, log-rate, and modified path models and methods for obtaining maximum likelihood estimates of the parameters of these models. Vermunt then shows how to incorporate variables with missing information in log-linear models for non-response. In addition, he covers such topics as the main types of hazard models; censoring; the use of time-varying covariates; models for competing risks; multivariate hazard models; and a general approach for dealing with missing data problems, including unobserved heterogeneity, measurement error in the dependent variable, measurement error in the covariate, partially missing information on the dependent variable, and partially observed covariate values.

 
Introduction
 
Log-Linear Anaylsis
 
Log-Linear Anaylsis with Latent Variables and Missing Data
 
Event History Analysis
 
Event History Analysis with Latent Variables and Missing Data
A: Computation of the Log-Linear Parameters When Using the IPF Algorithm  
B: The Log-Linear Model as One of the Generalized Linear Models  
C: The Newton-Raphson Algorithm  
D: The Uni-Dimensional Newton Algorithm  
E: Likelihood Equations for Modified Path Models  
F: The Estimation of Conditional Probabilities under Restrictions  
G: The Information Matrix in Modified Path Models with Missing Data  

"Log-Linear Models for Event Histories will be a welcome addition to the library of a statistician who wants an overview of methods for log-linear models and event history data." 

Theodore R. Holford
Yale University

Preview this book

For instructors

To inquire about the availability of this title for review (print and/or digital), please contact your local sales representative or call (800) 818-7243.

Select a Purchasing Option

ISBN: 9780761909378
$157.00