Author: Giovanni Parmigiani
Edition: 1
Publisher: Wiley
Binding: Hardcover
ISBN: 0471986089
Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice)
Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. Medical books Modeling in Medical Decision Making. 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 Medical books Modeling In Medical Decision Making: A Bayesian Approach (statistics In Practic. Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice) ISBN : 9780471986089 Title : Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice) Authors : Parmigiani, Giovanni Binding : Hardcover Publisher :
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Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice) ISBN : 9780471986089 Title : Modeling in Medical Decision Making: A Bayesian Approach (Statistics in Practice) Authors : Parmigiani, Giovanni Binding : Hardcover Publisher :
Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly Large amounts of data. InPreface. PART I: METHODS. 1. Inference. Summary. Medical Diagnosis. Genetic Counseling. Estimating sensitivity and specificity. Chronic
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
Categories: Bayes Theorem, Decision Support Techniques, Bayesian statistical decision theory. Contributors: Giovanni Parmigiani - Author. Format: Hardcover
Medical Book Modeling in Medical Decision Making
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.
