Event History Analysis with R

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