Author: Steve Selvin
Edition: 1
Binding: Paperback
ISBN: 0521719372
This practical guide shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. Download Survival Analysis for Epidemiologic and Medical Research (Practical Guides to Biostatistics and Epidemiology) from rapidshare, mediafire, 4shared. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival Search and find a lot of medical books in many category availabe for free download. Survival Analysis for Epidemiologic and Medical Research medical books pdf for free. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival
Edition: 1
Binding: Paperback
ISBN: 0521719372
This practical guide shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. Download Survival Analysis for Epidemiologic and Medical Research (Practical Guides to Biostatistics and Epidemiology) from rapidshare, mediafire, 4shared. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival Search and find a lot of medical books in many category availabe for free download. Survival Analysis for Epidemiologic and Medical Research medical books pdf for free. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival
Related books
Statistical Tools for Epidemiologic Research
In this innovative new book, Steve Selvin provides readers with a clear understanding of intermediate biostatistical methods without advanced mathematics or statistical theory (for example, no Bayesian statistics, no causal inference, no linear algeb
Survival Analysis: A Self-Learning Text, Third Edition (Statistics for Biology and Health)
An excellent introduction for all those coming to the subject for the first time. New material has been added to the second edition and the original six chapters have been modified. The previous edition sold 9500 copies world wide since its release i
Epidemiology: An Introduction
Across the last forty years, epidemiology has developed into a vibrant scientific discipline that brings together the social and biological sciences, incorporating everything from statistics to the philosophy of science in its aim to study and track
Statistics for Epidemiology
Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to cond
Tidak ada komentar:
Posting Komentar