Event History Analysis with R

Event History Analysis with R

Hardback Chapman & Hall/CRC Statistics in the Social and Behavioral S

By (author) Goran Brostrom

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  • Publisher: CRC Press Inc
  • Format: Hardback | 236 pages
  • Dimensions: 157mm x 236mm x 20mm | 440g
  • Publication date: 10 May 2012
  • Publication City/Country: Bosa Roca
  • ISBN 10: 1439831645
  • ISBN 13: 9781439831649
  • Edition statement: New.
  • Illustrations note: 75 black & white illustrations, 13 black & white tables
  • Sales rank: 752,135

Product description

With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. Features * Introduces parametric proportional hazards models with baseline distributions like the Weibull, Gompertz, Lognormal, and Piecewise constant hazard distributions, in addition to traditional Cox regression * Presents mathematical details as well as technical material in an appendix * Includes real examples with applications in demography, econometrics, and epidemiology * Provides a dedicated R package, eha, containing special treatments, including making cuts in the Lexis diagram, creating communal covariates, and creating period statistics A much-needed primer, Event History Analysis with R is a didactically excellent resource for students and practitioners of applied event history and survival analysis.

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Author information

Goran Brostrom is a professor emeritus of statistics in the Centre for Population Studies at Umea University in Sweden.

Review quote

"This book in The R Series from Chapman & Hall acts much as a companion to the R package eha by the same author. ... If one wants to analyse such data using R, then the book is well worthwhile. Although it is written more from the point of view of a reader comfortable in using R [and] wanting to learn more about demographic data, it also offers something for the demographer looking to extend the scope of their analyses. ... the depth of treatment is about right to form the core of a lecture course ..." -Mark Bebbington, Australian & New Zealand Journal of Statistics, 2013

Table of contents

Preface Event History and Survival Data Introduction Survival Data Right Censoring Left Truncation Time Scales Event History Data More Data Sets Single Sample Data Introduction Continuous Time Model Descriptions Discrete Time Models Nonparametric Estimators Doing it in R Cox Regression Introduction Proportional Hazards The Log-Rank Test Proportional Hazards in Continuous Time Estimation of the Baseline Hazard Explanatory Variables Interactions Interpretation of Parameter Estimates Proportional Hazards in Discrete Time Model Selection Male Mortality Poisson Regression Introduction The Poisson Distribution The Connection to Cox Regression The Connection to the Piecewise Constant Hazards Model Tabular Lifetime Data More on Cox Regression Introduction Time-Varying Covariates Communal covariates Tied Event Times Stratification Sampling of Risk Sets Residuals Checking Model Assumptions Fixed Study Period Survival Left- or Right-Censored Data Parametric Models Introduction Proportional Hazards Models Accelerated Failure Time Models Proportional Hazards or AFT Model? Discrete Time Models Multivariate Survival Models Introduction Frailty Models Parametric Frailty Models Stratification Competing Risks Models Introduction Some Mathematics Estimation Meaningful Probabilities Regression R Code for Competing Risks Causality and Matching Introduction Philosophical Aspects of Causality Causal Inference Aalen's Additive Hazards Model Dynamic Path Analysis Matching Conclusion Basic Statistical Concepts Introduction Statistical Inference Asymptotic theory Model Selection Survival Distributions Introduction Relevant Distributions in R Parametric Proportional Hazards and Accelerated Failure Time Models A Brief Introduction to R R in General Some Standard R Functions Writing Functions Graphics Probability Functions Help in R Functions in eha and survival Reading Data into R Survival Packages in R Introduction eha survival Other Packages Bibliography Index