Survival Analysis: Techniques for Censored and Truncated Data (Statistics for Biology and Health)
| Author | : | |
| Rating | : | 4.32 (809 Votes) |
| Asin | : | 038795399X |
| Format Type | : | paperback |
| Number of Pages | : | 538 Pages |
| Publish Date | : | 2014-04-24 |
| Language | : | English |
DESCRIPTION:
Technical details of the derivation of the techniques are sketched in a series of Technical Notes. Applied statisticians in many fields must frequently analyze time to event data. The prerequisite is a standard course in statistical methodology.. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex methods more accessible to applied researchers without an advanced mathematical background. The analysis of survival experiments is complicated by issues of censoring, where an individual's life length is known to occur only in a certain period of time, and by truncation, where individuals enter the study only if they survive a sufficient length of time or individuals are included in the study only if the event has occurred by a given date. The authors present the essence of these techniques, as well as classical techniques not based on counting processes, and apply them to data. This book will be useful for investigators who need to analyze censored or truncated life time data, and as a textbook for a graduate course in survival analysis. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on ap
pretty good text but the examples/problems go downhill near the end David I used this book for a class in survival analysis (a graduate level biostats course) and I found it very useful. Much of the first several chapters are fairly quick relative to many graduate statistics texts and focuses on application with less emphasis on theory. Overall, I have no major qualms with the book. The author goes on a bit longer than necessary but I'd rather end up skimming text than be stuck deciphering terse material. This extra explanation also opens the book up to a wider audience.A solid understanding of basic statistics is necessary to get started in this book. To get more, 4+ semester-long statistics courses, at le. Good Book I am a computer scientist and using this book for my research to address a problem. This book is well written but of course target audience are people with solid background in probability theory and parameteric estimation (pattern recognition). Therefore please do not expect that author will teach you basic probability theory. Contents are more applied in nature therefore natural audience are staticians and researchers.. A good book of studying Survival Analysis In this new edition, many errata are corrected and each of the theories has a reason why this is true. Although they may be more practical in view, it is very good to use them to learn Survival Analysis, which is more realistic in sense.In its Theoretical Notes and Practical Notes, there are a lot of different views and sights to show that which is the best to use. The examples are more or less good one and explained in a more detailed way than that in the 1st edition. A good-buy and must-read for those want to have a thorough view in this aspects. Read them carefully! Better than Cox's in this new edition. Buy and read this new editi