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Log-Linear Models for Event Histories

Log-Linear Models for Event Histories

June 1997 | 360 pages | SAGE Publications, Inc
Event history analysis has been a useful method in the social sciences for studying the processes of social change. However, a main difficulty in using this technique is to observe all relevant explanatory variables without missing any variables.

This book presents a general approach to missing data problems in event history analysis which is based on the similarities between log-linear models, hazard models and event history models. It begins with a discussion of log-rate models, modified path models and methods for obtaining maximum likelihood estimates of the parameters of log-linear models. The author then shows how to incorporate variables with missing information in log-linear models - including latent class models, modified path models with latent variables and log-linear models for non-response. Other topics covered are: 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 measurement error in the dependent variable, measurement error in the covariates, partially missing information in the dependent variable and partially observed covariate values.

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

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ISBN: 9780761909378