Log-Linear Models for Event Histories - Advanced Quantitative Techniques in the Social Sciences (Hardback)Jeroen K. Vermunt (author)
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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.
Publisher: SAGE Publications Inc
Number of pages: 360
Weight: 710 g
Dimensions: 228 x 152 x 33 mm
"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
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