Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice) - Tapa dura

Parmigiani

 
9780471986089: Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice)
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ISBN 10: 0471986089 ISBN 13: 9780471986089
Editorial: John Wiley & Sons, 2002

Sinopsis

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing have led to a host of new and powerful statistical tools to support decision making. Simulation-based Bayesian methods are especially promising, as they provide a unified framework for data collection, inference, and decision making. In addition, these methods are simple to interpret, and can help to address the most pressing practical and ethical concerns arising in medical decision making.
* Provides an overview of the necessary methodological background, including Bayesian inference, Monte Carlo simulation, and utility theory.
* Driven by three real applications, presented as extensively detailed case studies.
* Case studies include simplified versions of the analysis, to approach complex modelling in stages.
* Features coverage of meta-analysis, decision analysis, and comprehensive decision modeling.
* Accessible to readers with only a basic statistical knowledge.
Primarily aimed at students and practitioners of biostatistics, the book will also appeal to those working in statistics, medical informatics, evidence-based medicine, health economics, health services research, and health policy.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Giovanni Parmigiani is the author of Modeling in Medical Decision Making: A Bayesian Approach, published by Wiley.

De la contraportada

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing power have led to a host of new and powerful statistical tools to support decision making. Simulation-based Bayesian methods are especially promising, as they provide a unified framework for data collection, inference, and decision making. In addition, these methods are simple to implement and can help to address the most pressing practical and ethical concerns arising in medical decision making.
* Provides an overview of the necessary methodological background, including Bayesian inference, Monte Carlo simulation, and utility theory.
* Driven by three real applications, presented as extensively detailed case studies.
* Case studies include simplified versions of the analysis, to approach complex modelling in stages.
* Features coverage of meta-analysis, decision analysis, and comprehensive decision modeling.
* Accessible to readers with only a basic statistical knowledge.
Primarily aimed at students and practitioners of biostatistics, the book will also appeal to those working in statistics, medical informatics, evidence-based medicine, health economics, health service research and health policy.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
John Wiley & Sons
Año de publicación
2002
Idioma
Inglés
ISBN 10 
0471986089
ISBN 13 
9780471986089
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
280
Contacto del fabricante
no disponible
Persona responsable
no disponible