Log-Linear Models for Event Histories

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.

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