Event History Analysis with R

Regular price €107.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Goran Brostrom
Accelerated Failure Time Models
advanced event history analysis in R
Aft
Author_Goran Brostrom
Baseline Cumulative Hazard
Baseline Hazard Function
Birth Intervals
Category=GPS
Category=JHBC
Category=JMB
Category=PBT
causality
cohort statistics
competing risks
Cox Regression
Cox Regression Model
Cumulative Distribution Function
Cumulative Hazard Functions
Cumulative Hazards
Data Set
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Event History Analysis
event survival analysis
Frailty Model
Gompertz Distribution
Hazard Function
incomplete data analysis
Left Truncation
Lexis Diagram
LRT
Martingale Residuals
multivariate survival models
parametric models
Poisson regression
Proportional Hazards
Proportional Hazards Family
Proportional Hazards Model
R
R package
register-based data
Regression Model
reproducible research
Risk Set
Rstudio
social science statistics
statistical computing environment
survival analysis
Survival Functions
time-to-event modeling

Product details

  • ISBN 9781138587717
  • Weight: 740g
  • Dimensions: 156 x 234mm
  • Publication Date: 11 Nov 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

With an emphasis on social science applications, Event History Analysis with R, Second Edition, presents an introduction to survival and event history analysis using real-life examples. Since publication of the first edition, focus in the field has gradually shifted towards the analysis of large and complex datasets. This has led to new ways of tabulating and analysing tabulated data with the same precision and power as that of an analysis of the full data set. Tabulation also makes it possible to share sensitive data with others without violating integrity.

The new edition extends on the content of the first by both improving on already given methods and introducing new methods. There are two new chapters, Explanatory Variables and Regression, and Register- Based Survival Data Models. The book has been restructured to improve the flow, and there are significant updates to the computing in the supporting R package.

Features

• Introduction to survival and event history analysis and how to solve problems with incomplete data
using Cox regression.
• Parametric proportional hazards models, including the Weibull, Exponential, Extreme Value, and
Gompertz distributions.
• Parametric accelerated failure time models with the Lognormal, Loglogistic, Gompertz, Exponential,
Extreme Value, and Weibull distributions.
• Proportional hazards models for occurrence/exposure data, useful with tabular and register based data,
often with a huge amount of observed events.
• Special treatments of external communal covariates, selections from the Lexis diagram, and creating
period as well as cohort statistics.
• “Weird bootstrap” sampling suitable for Cox regression with small to medium-sized data sets.
• Supported by an R package (https://CRAN.R-project.org/package=eha), including code and data for
most examples in the book.
• A dedicated home page for the book at http://ehar.se/r/ehar2

This substantial update to this popular book remains an excellent resource for researchers and practitioners
of applied event history analysis and survival analysis. It can be used as a text for a course for graduate
students or for self-study.

Göran Broström is professor emeritus of Statistics at the Centre for Demographic and Ageing Research, Umeå University. He has a PhD in mathematical statistics from Umeå University (1979). He is the author of two R packages, eha and glmmML, available on CRAN.

More from this author