Recursive Partitioning in the Health Sciences (Statistics for Biology and Health)

Manufacturer: Springer Availability: Usually ships in 24 hours List Price:$109.00 Our Price:$87.00 Authors: Heping Zhang Burton Singer Description:

Reviews:

a fitting sequel to CART with emphasis on the health science applications
Brieman, Olshen, Friedman and Stone introduced CART in their 1984 book. It is an effective methodology and software tool for constructin classification and regression trees. The procedure is also referred to as recursive partitioning.

There has been a great deal of research over the past 16 on this topic and the authors cover the basics and the new material well. New ideas include survival trees and adaptive splines (including MARS). It provides interesting applications to health science problems. Th authors compare tree based methods to logistic regression. This is a notable successor to the CART text.

It is a little more difficult to read then CART. CART was motivated by biomedical problems but the book covered other applications in business and pattern recognition as well. This texts puts an emphasis on the important medical applications.


sequel to CART
Brieman, Olshen, Friedman and Stone introduced CART in their 1984 book. It is an effective methodology and software tool for constructin classification and regression trees. The procedure is also referred to as recursive partitioning. There has been a great deal of research over the past 16 on this topic and the authors cover the basics and the new material well. New ideas include survival trees and adaptive splines (including MARS). It provides interesting applications to health science problems. Th authors compare tree based methods to logistic regression. This is a notable successor to the CART text.


Recursive Partitioning in the Health Sciences
Zhang and Singer have done a splendid job of explaining recursive partitioning, a topic that should be of great interest to anyone who wants to make sense of data in which there are many potentially important variables contributing to some outcome or variable of interest. One should not be put off by the "... in the Health Sciences" part of the book's title; the potential audience of readers who can benefit from reading it is much greater than this implies (I'm an ecologist, for example). Why? First, because the topics covered have wide applicability in many fields; and second, because the writing is exceptionally clear and easy to follow. If you are able to use a typical introductory text on multiple regression, for example, you should have no difficulty getting a lot out of Zhang and Singer. If you are able to handle a mathematically rigorous approach to statistics but are new to the topics covered here, this book will provide an excellent starting place before you jump into the many references to the recent literature provided by the authors.


Recursive Partitioning
To divide ricorsivo in health sciences is one of the little statistical witnesses specifically written with the epidemiologo like final utilizzatore of the objective, similar in the kind to the studies of control of case of the Schlesselman. The topic is relatively new in the field of the epidemiologia and like such necessities of being reported contextually to the more traditional statistical methods. The introductory authors complete this comprising the understood one them on the methods that correspond to that they are recalls to you with the not parametrali methods to divide ricorsivo and of adaptable rabbets more variable than regression (MARS). Ulteriorly, this compare turn out to you between try and true statistical methods to you and to divide ricorsivo and MARS to many examples illustrated to you. This last one is one resistance of this book. The examples of every subject in argument are consider you with attention in a way graduate them. The book pleasantly is balanced in terms of teoretica low priority and practical applications, with the generally comprehensible writing to the not-statistical one. The book has supplied to our group the base material in order to allow the use to divide ricorsivo in our search. While the technique to divide ricorsivo is recognized and subsequently applied in the field epidemiologist, this book can gush transforma in in a classic.


Recursive Partitioning
To divide ricorsivo in health sciences is one of the little statistical witnesses specifically written with the epidemiologo like final utilizzatore of the objective, similar in the kind to the studies of control of case of the Schlesselman. The topic is relatively new in the field of the epidemiologia and like such necessities of being reported contextually to the more traditional statistical methods. The introductory authors complete this comprising the understood one them on the methods that correspond to that they are recalls to you with the not parametrali methods to divide ricorsivo and of adaptable rabbets more variable than regression (MARS). Ulteriorly, this compare turn out to you between try and true statistical methods to you and to divide ricorsivo and MARS to many examples illustrated to you. This last one is one resistance of this book. The examples of every subject in argument are consider you with attention in a way graduate them. The book pleasantly is balanced in terms of teoretica low priority and practical applications, with the generally comprehensible writing to the not-statistical one. The book has supplied to our group the base material in order to allow the use to divide ricorsivo in our search. While the technique to divide ricorsivo is recognized and subsequently applied in the field epidemiologist, this book can gush transforma in in a classic.



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