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Bayesian Cost-Effectiveness Analysis of Medical Treatments (Paperback)
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Bayesian Cost-Effectiveness Analysis of Medical Treatments (Paperback)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 19 working days
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Cost-effectiveness analysis is becoming an increasingly important
tool for decision making in the health systems. Cost-Effectiveness
of Medical Treatments formulates the cost-effectiveness analysis as
a statistical decision problem, identifies the sources of
uncertainty of the problem, and gives an overview of the
frequentist and Bayesian statistical approaches for decision
making. Basic notions on decision theory such as space of
decisions, space of nature, utility function of a decision and
optimal decisions, are explained in detail using easy to read
mathematics. Features Focuses on cost-effectiveness analysis as a
statistical decision problem and applies the well-established
optimal statistical decision methodology. Discusses utility
functions for cost-effectiveness analysis. Enlarges the class of
models typically used in cost-effectiveness analysis with the
incorporation of linear models to account for covariates of the
patients. This permits the formulation of the group (or subgroup)
theory. Provides Bayesian procedures to account for model
uncertainty in variable selection for linear models and in
clustering for models for heterogeneous data. Model uncertainty in
cost-effectiveness analysis has not been considered in the
literature. Illustrates examples with real data. In order to
facilitate the practical implementation of real datasets, provides
the codes in Mathematica for the proposed methodology. The
motivation for the book is to make the achievements in
cost-effectiveness analysis accessible to health providers, who
need to make optimal decisions, to the practitioners and to the
students of health sciences. Elias Moreno is Professor of
Statistics and Operational Research at the University of Granada,
Spain, Corresponding Member of the Royal Academy of Sciences of
Spain, and elect member of ISI. Francisco Jose Vazquez-Polo is
Professor of Mathematics and Bayesian Methods at the University of
Las Palmas de Gran Canaria, and Head of the Department of
Quantitative Methods. Miguel Angel Negrin is Senior Lecturer in the
Department of Quantitative Methods at the ULPGC. His main research
topics are Bayesian methods applied to Health Economics, economic
evaluation and cost-effectiveness analysis, meta-analysis and
equity in the provision of healthcare services.
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