| Description |
1 online resource (viii, 300 pages) |
| Contents |
Event History Analysis With Stata; Copyright; Contents; Preface; Chapter 1 Introduction; 1.1 Causal Modeling and Observation Plans; 1.1.1 Cross-Sectional Data; 1.1.2 Panel Data; 1.1.3 Event History Data; 1.2 Event History Analysis and Causal Modeling; Chapter 2 Event History Data Structures; 2.1 Basic Terminology; 2.2 Event History Data Organization; Chapter 3 Nonparametric Descriptive Methods; 3.1 Life Table Method; 3.2 Product-Limit Estimation; 3.3 Comparing Survivor Functions; Chapter 4 Exponential Transition Rate Models; 4.1 The Basic Exponential Model; 4.1.1 Maximum Likelihood Estimation |
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4.1.2 Models without Covariates4.1.3 Time-Constant Covariates; 4.2 Models with Multiple Destinations; 4.3 Models with Multiple Episodes; Chapter 5 Piecewise Constant Exponential Models; 5.1 The Basic Model; 5.2 Models without Covariates; 5.3 Models with Proportional Covariate Effects; 5.4 Models with Period-Specific Effects; Chapter 6 Exponential Models with Time-Dependent Covariates; 6.1 Parallel and Interdependent Processes; 6.2 Interdependent Processes: The System Approach; 6.3 Interdependent Processes: The Causal Approach; 6.4 Episode Splitting with Qualitative Covariates |
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6.5 Episode Splitting with Quantitative Covariates6.6 Application Examples; Chapter 7 Parametric Models of Time-Dependence; 7.1 Interpretation of Time-Dependence; 7.2 Gompertz Models; 7.3 Weibull Models; 7.4 Log-Logistic Models; 7.5 Log-Normal Models; Chapter 8 Methods to Check Parametric Assumptions; 8.1 Simple Graphical Methods; 8.2 Pseudoresiduals; Chapter 9 Semiparametric Transition Rate Models; 9.1 Partial Likelihood Estimation; 9.2 Time-Dependent Covariates; 9.3 The Proportionality Assumption; 9.4 Baseline Rates and Survivor Functions; 9.5 Application Example |
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Chapter 10 Problems of Model Specification10.1 Unobserved Heterogeneity; 10.2 Models with a Mixture Distribution; 10.2.1 Models with a Gamma Mixture; 10.2.2 Exponential Models with a Gamma Mixture; 10.2.3 Weibull Models with a Gamma Mixture; 10.3 Discussion; References; About the Authors; Index |
| Summary |
Event History Analysis With Stata provides an introduction to event history modeling techniques using Stata (version 9), a widely used statistical program that provides tools for data analysis. The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data, to data organization, to applications using the software, to the interpretation of results. T |
| Bibliography |
Includes bibliographical references (pages 271-292) and index |
| Notes |
Print version record |
| SUBJECT |
Stata. http://id.loc.gov/authorities/names/n88156843
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Stata. fast (OCoLC)fst01375322 |
| Subject |
Event history analysis.
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REFERENCE -- Research.
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Event history analysis.
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Event history analysis.
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| Form |
Electronic book
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| Author |
Golsch, Katrin.
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Rohwer, Götz.
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| ISBN |
1410614298 |
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9781410614292 |
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9781135595937 |
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1135595933 |
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9781135595920 |
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1135595925 |
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