The Encyclopaedic Companion to Medical Statistics

In recent years the central importance of appropriate statistical methodology has been increasingly recognised in research studies in medicine and also in day–to–day clinical practice.
Medical literature is now liberally punctuated not only with relatively routine statistical terms such as ′p–value′, ′t–test′ and ′confidence interval′, but also with more esoteric items such as ′hazard function, ′multilevel model′ and ′generalised estimating equations′. Consequently, researchers in medicine and clinicians who are not primarily Statisticians need to have a source that provides readable accounts of these terms so that they can better understand Statistical aspects of both the design and analysis of a reported investigation.
The Encyclopaedic Companion to Medical Statistics aims to be that source, containing readable accounts of almost 400 statistical topics central to current medical research. Each entry has been written by an individual chose for both their expertise in the field and their ability to communicate Statistical concepts successfully to medical researchers. real examples from the biomedical literature and relevant illustrations feature in many entries, and extensive cross–referencing signposts the reader to related entries.
"If this magnificent encyclopaedia can be deployed in the ongoing argument about the future of twenty–first century academic medicine, then not only the research enterprise but also the public′s health and well–being will be far stronger tomorrow than it is today."
—Richard Horton, Editor, The Lancet

Spis treści:
Foreword.
Preface.
Biographical Information on the Editors.
List of Contributors.
Abbreviations and Acronyms.
The Encyclopaedic Companion to Medical Statistics.

Nota biograficzna:
Brian S. Everitt – Professor Emeri tus, King′s College London. After 35 Years at the Institute of Psychiatry, University of London, Brian Everitt retired in May 2004. Author of approximately 100 journal articles and over 50 books on statistics, and also –co–editor of Statistical Methods in Medical Research. Writing continues apace in retirement but now punctuated by tennis, walks in the country, guitar playing and visits to the gym, rather than by committees, committees and more committees.
Christopher R. Palmer, founding Director of Cambridge University′s Centre for Applied Medical Statistics, regularly teaches and collaborates with current and future doctors. His first degree was from Oxford, while graduate and post–doctoral studies were in the USA (at UNC–Chapel Hill and Harvard). He has shifted from mathematical towards applied statistics, with particular interest in the ethics of clinical trials and the use of flexible designs whenever appropriate. Fundamentally, he likes to promote sound statistical thinking in all areas of medical research and hopes this volume might help towards that end. Chris served as Deputy or Acting Editor of Statistics in Medicine, 1996–2000, and is a long–standing statistical reviewer for The Lancet. he and his wife have three children they consider to be more than Statistically significant.

Okładka tylna:
In recent years the central importance of appropriate statistical methodology has been increasingly recognised in research studies in medicine and also in day–to–day clinical practice.
Medical literature is now liberally punctuated not only with relatively routine statistical terms such as ′p–value′, ′t–test′ and ′confidence interval′, but also with more esoteric items such as ′hazard function, ′multilevel model′ and ′generalised estimating equations′. Consequently, researchers in medicine and clinicians who are not primarily Statisticians need to have a source that provides readable accounts of these terms so that they can better understand Statistical aspects of both the design and analysis of a reported investigation.
The Encyclopaedic Companion to Medical Statistics aims to be that source, containing readable accounts of almost 400 statistical topics central to current medical research. Each entry has been written by an individual chose for both their expertise in the field and their ability to communicate Statistical concepts successfully to medical researchers. real examples from the biomedical literature and relevant illustrations feature in many entries, and extensive cross–referencing signposts the reader to related entries.
"If this magnificent encyclopaedia can be deployed in the ongoing argument about the future of twenty–first century academic medicine, then not only the research enterprise but also the public′s health and well–being will be far stronger tomorrow than it is today."
—Richard Horton, Editor, The Lancet