This book is for anyone who wants to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. 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 and Event History Analysis allows researchers to quickly master advanced statistical techniques. Moreover, 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 and Event History Analysis covers up-to-date innovations in the field, including advancements in the assessment of model fit, frailty and recurrent events, discrete-time, multistate models and sequence analysis. Practical instructions are also included for using the statistical programs of R and STATA, enabling readers to replicate the examples described in the text.
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“This is a great text book to learn survival and event-history analysis with a basis in R…. I highly recommended it for both R users and demographers!”
“Survival Analysis sucks, but this writer tries to break it down as much as possible.”
“All chapters provided detailed and clear conceptual explanations that you can easily follow. Besides, historical comments offer insights about the origins and ratioinale behind fundamental methods, which helps you understand their applicability and limitations. R code is provided to illustrate example cases, as well as really useful summaries of available procedures and workflows, including notes on how to choose the adequate method for each situation and why. In summary, a self-contained and extremely valuable resource to get yourself introduced to survival and event history analysis.”
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