Introducing Survival and Event History Analysis - Softcover

in different scientific areas – social sciences and humanities, medicine, in

general every science where studies measuring time changes in variables are

conducted...As the author explains, this book is written from the

perspective of an absolute beginner – comprehensible and with a lot of examples

in the text, tables and graphs. It goes beyond an introductory textbook on this

topic, because it presents not only non-parametric models, semi-parametric

models, parametric models, model-building and model diagnostics, but it is focused also on some more recent techniques like frailty and recurrent event

history models, discrete-time models, multistate models, competing risk

analysis and sequence analysis...Everyone who would like to start with Survival and

Event History analysis or to get more knowledge of Survival and Event History

analysis could do this by reading this book
Stanislava Yordanova Stoyanova
Methodspace

Introducing Survival Analysis and Event History Analysis is an accessible, practical and comprehensive guide for researchers and students who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics.

Engaging, easy to read, functional and packed with enlightening examples, 'hands-on' exercises and resources for both students and instructors, Introducing Survival Analysis and Event History Analysis allows researchers to quickly master these advanced statistical techniques. This book is written from the perspective of the 'user', making it suitable as both a self-learning tool and graduate-level textbook.

Introducing Survival Analysis and Event History Analysis covers the most up-to-date innovations in the field, including advancements in the assessment of model fit, frailty and recurrent event models, discrete-time methods, competing and multistate models and sequence analysis. Practical instructions are also included, focusing on the statistical program R and Stata, enabling readers to replicate the examples described in the text.

This book comes with a glossary, a range of practical and user-friendly examples, cases and exercises.