Event History Analysis
SAGE, 1991. 7. 18. - 182페이지
"In a manner similar to many other titles within the Applied Social Research Methods Series, this 182-page book thoroughly covers many of the specific methodological hurdles encountered in implementing event history analysis (EHA). The Applied Social Research Methods Series' ... is the result of careful subject selection. ... Consistent with the practical orientation of the book, each of the application sections provides useful insights into data structure problems and programming notes. ... Kazuo Yamaguchi's insightful review of problems in structuring EHA models is useful for those contemplating life-course research. ... We strongly recommend its inclusion in the libraries of marketing researchers and its inclusion on suggested reading lists of graduate research method seminars."--Journal of Marketing Research "This book, which is part of Sage Publications' Applied Social Research Methods Series, is a practical guide for those interested in using event history analysis. ... The book's strength is that it is well written and easy to understand. Even those with limited statistical backgrounds can follow the discussion and the systematic progression from the simpler to the more complex models (although the author provides ample references for those wanting a more rigorous discussion). ... Upon finishing the book, I found myself wondering about specific accounting questions that might be addressed using event history analysis. There are many, and in fact, most issues can be recast in an events framework. ... In sum, I recommend this book to anyone wanting to use event history analysis whether to apply to new research questions or to provide a fresh look at old questions." --The Accounting Review "A significant introduction to the event-history literature that provides the background to implement this difficult methodology successfully and that can be supplemented with other, more advanced texts. It will undoubtedly become a prized text among students and a valuable reference for the research community." --Contemporary Sociology As a research tool event history analysis has recently become a key technique for researchers, professionals and students in a wide range of disciplines. However, despite this increasing interest, few resources exist which clearly examine this technique. Now, Event History Analysis provides a systematic introduction to models, methods and applications of event history analysis. Kazuo Yamaguchi emphasizes "hands on" information, including the use and misuse of samples, models, and covariates in applications, the structural arrangement of input data, the specification of various models in such computer programs as SAS-LOGIST and SPSS-LOGLINEAR, and the interpretation of parameters estimated from models. This timely book also offers such significant topics as missing data, hazard rate, Cox's partial likelihood model, survivor function, and discrete-time logit models for both one-way and two-way transitions. Event History Analysis is essential for researchers, professionals and students of public health, sociology, labor economics, political science, and organization studies.-Provided by published.
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ContinuousTime Models with Coxs Method
Construction of Input Data
A Misuse in the Distinction Between
LogRate Models for Piecewise Constant Rates
ards Models and Stratified Models
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age cohort age effects age of employment assume becomes BMDP2L BMDPLR censored observations chapter characterization chi-square coefficient compared conditional probabilities continuous-time cross-classified defined DEP1 DEP2 dependent variable discrete time points discrete-time logit models discrete-time models distinct dummy variables duration dependence duration effect effects of age employ entry event history analysis example explanatory variables fects Formula getting married given hazard function hazard rate hazard-rate Hence hypotheses indicates input data interaction effects interfirm job separation L_EMP level of personal life-course likelihood function likelihood-ratio test lines log-odds log-rate models logistic regression main effects marriage method Model 13 nested models occurrence Panel parameter estimates premarital presented proportional hazards models proportional odds model rates of interfirm repeatable events represents RESEARCH risk period sample saturated model selection bias specifies spells subjects survey survivor function Table time-dependent covariates tion two-way transitions U_EMP UEMP values versus Wald test Yamaguchi zero