Introducing Survival and Event History Analysis
| Author | : | |
| Rating | : | 4.75 (799 Votes) |
| Asin | : | 1848601026 |
| Format Type | : | paperback |
| Number of Pages | : | 300 Pages |
| Publish Date | : | 2016-11-17 |
| Language | : | English |
DESCRIPTION:
"Great!" according to Annyanka. This is a great text book to learn survival and event-history analysis with a basis in R. Apart from the formulas behind the different models everything else is explained in a fairly simple manner, and almost every step on how to do stuff is shown with examples in R codes. I highly recommended it for both R users and demographers!. J. Felipe Ortega Soto said Best introduction to survival analysis. This books provides a concise and clear introduction to survival and event history analysis, including descriptive non-parametric methods, Cox proportional hazards, parametric models and model assessment. It also covers models for frailty and recurrent events, discrete-time models and competing risks and multi-state models. The final chapter introduces sequence analysis, which is not covered in alternative books on this subject.All chapters provided detailed and clear conceptual ex. "Easy to understand" according to burgla. Survival Analysis sucks, but this writer tries to break it down as much as possible. I read my textbook and can't understand a thing, then I read this book and at least kind of get what's going on.
This book is very useful for researchers and studentsin different scientific areas – social sciences and humanities, medicine, ingeneral every science where studies measuring time changes in variables areconductedAs the author explains, this book is written from theperspective of an absolute beginner – comprehensible and with a lot of examplesin the text, tables and graphs. It goes beyond an introductory textbook on thistopic, because it presents not only non-parametric models, semi-parametricmodels, parametric models, model-building and model diagnostics, but it is focused also on some more recent techniques like frailty and recurrent eventhistory models, discrete-time models, multistate models, competing riskanalysis and sequence analysisEveryone who would like to start with Survival andEvent History analysis or to get more knowledge of Survival and Event Historyanalysis could do this by reading this bookStanisla
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, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the 'user', making it suitable as both a self-learning tool and graduate-level textbook.Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models.