Log-linear models for event histories

著者

• Vermunt, Jeroen K.

書誌事項

Log-linear models for event histories

Jeroen K. Vermunt

（Advanced quantitative techniques in the social sciences, 8）

Sage Publications, c1997

注記

Includes bibliographical references (p.319-333) and indexes

収録内容

• Introduction
• Log-linear analysis
• Long-linear analysis with latent variables and missing data
• Event history analysis
• Event history analysis with latent variables and missing data

内容説明・目次

内容説明

Event history analysisua method for explaining why some people are more likely to experience a particular event, transition, or change than other peopleuhas 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.

目次

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

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BA30775900
• ISBN:
  • 0761909370
• LCCN: 97004805
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Thousand Oaks, Calif.
• ページ数/冊数: x, 348 p.
• 大きさ: 24 cm
• 分類:
  • LCC : QA278
  • DC21 : 519.5/35
• 件名:
  • LCSH : Log-linear models
  • LCSH : Longitudinal method -- Statistical methods
• 親書誌ID:
  • BA14307479