Recursive partitioning in the health sciences信息编码、析取与分配的数学 pdf epub mobi txt 电子书 下载 2024


Recursive partitioning in the health sciences信息编码、析取与分配的数学

简体网页||繁体网页
Zhang, Heping/ Singer, Burton
Springer Verlag
1999-3
226
813.00元
HRD
9780387986715

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Recursive partitioning in the health sciences信息编码、析取与分配的数学 epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

Recursive partitioning in the health sciences信息编码、析取与分配的数学 epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

Recursive partitioning in the health sciences信息编码、析取与分配的数学 pdf epub mobi txt 电子书 下载 2024



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This book describes the recursive partitioning methodology and demonstrates its effectiveness as a response to the challenge of analyzing and interpreting multiple complex pathways to many illnesses, diseases, and ultimately death. For comparison purposes, standard regression methods are presented briefly and they are applied in the examples. We emphasize particularly the importance of scientific judgment and interpretation while guided by statistical output. This book is suitable for three broad groups of readers: biomedical researchers, clinicians, public health practitioners including epidemiologists, health service researchers, environmental policy advisers; consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients' problems; and statisticians interested in methodological and theoretical issues.This book provides an up-to-date summary of the methodological and theoretical underpinnings of recursive partitioning. It also presents a host of unsolved problems whose solutions would advance the rigorous underpinnings of statistics in general. Heping Zhang is Associate Professor of Biostatistics and Child Study at Yale University. In addition to the methodology and application of recursive partitioning, he is interested in developing statistical methods for analyzing correlated data, especially family and genetic studies, and brain imaging problems. Burton Singer, a member of the National Academy of Sciences, is Professor of Demography and Public Affairs at Princeton University. His research interests include combinatorial formulation of randomness, infectious disease epidemiology, and bio-demography of aging.

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