Log-Linear Models for Event Histories

1. Auflage 1997
ISBN: 978-0-7619-0937-8
Verlag: Sage Publications, Inc

Buch, Englisch, Band 8, 360 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 675 g

Reihe: Advanced Quantitative Techniques in the Social Sciences

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.

Autoren/Hrsg.

Vermunt, Jeroen K.

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

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

Über Autor(innen)

Vermunt, Jeroen K.
Jeroen K. Vermunt is a full professor in the Department of Methodology and Statistics at Tilburg University, the Netherlands. His research is on methodology of social, behavioral, and biomedical research, with a special focus on latent variable models and techniques for the analysis of categorical, multilevel, and longitudinal data sets. He has widely published on these topics in statistical and methodological journals and has also coauthored many articles in applied journals in which these methods are used to solve practical research problems. He is the codeveloper (with Jay Magidson) of the Latent GOLD software package. In 2005, Vermunt was awarded the Leo Goodman award by the Methodology Section of the American Sociological Association. His full CV and publications can be found at www.jeroenvermunt.nl.