Modeling in Medical Decision Making: A Bayesian Approach / Edition 1

Modeling in Medical Decision Making: A Bayesian Approach / Edition 1

by Giovanni Parmigiani, G. Parmigiani
     
 

ISBN-10: 0471986089

ISBN-13: 9780471986089

Pub. Date: 03/20/2002

Publisher: Wiley

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

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Overview

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.

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Product Details

ISBN-13:
9780471986089
Publisher:
Wiley
Publication date:
03/20/2002
Series:
Statistics in Practice Series
Pages:
280
Product dimensions:
6.28(w) x 9.37(h) x 0.82(d)

Table of Contents

Preface.

PART I: METHODS.

1. Inference.

Summary.

Medical Diagnosis.

Genetic Counseling.

Estimating sensitivity and specificity.

Chronic disease modeling.

2. Decision making.

Summary.

Foundations of expected utility theory.

Measuring the value of avoiding a major stroke.

Decision making in health care.

Cost-effectiveness analyses in the μ SPPM.

Statistical decision problems.

3. Simulation.

Summary.

Inference via simulation.

Prediction and expected utility via simulation.

Sensitivity analysis via simulation.

Searching for strategies via simulation.

Part II: CASE STUDIES.

4. Meta-analysis.

Summary.

Meta-analysis.

Bayesian meta-analysis.

Tamoxifen in early breast cancer.

Combined studies with continuous and dichotomous responses.

Migraine headache.

5. Decision trees.

Summary.

Axillary lymph node dissection in early breast cancer.

A simple decision tree

A more complete decision tree for ALND

6. Chronic disease modeling.

Summary.

Model overview.

Natural history model.

Modeling the effects of screening.

Comparing screening schedules.

Model critique.

Optimizing screening schedule.

References

Index.

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