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Bayesian Cost-effectiveness Analysis of Medical Treatments

Bayesian Cost-effectiveness Analysis of Medical Treatments (Hardcover)

Elias Moreno, Francisco Jose Vazquez-polo, Miguel Angel Negrin-hernandez (지은이)
Chapman & Hall
284,620원

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Bayesian Cost-effectiveness Analysis of Medical Treatments
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책 정보

· 제목 : Bayesian Cost-effectiveness Analysis of Medical Treatments (Hardcover) 
· 분류 : 외국도서 > 경제경영 > 일반
· ISBN : 9781138731738
· 쪽수 : 300쪽
· 출판일 : 2019-01-29

목차

  1. Health economics evaluation
  2. Introduction

    Conventional types of economic evaluation

    The variables of cost-effectiveness analysis

    Sources of uncertainty in cost-effectiveness analysis

    Conventional tools for cost-effectiveness analysis

    The incremental cost-effectiveness ratio

    The incremental net benefit

    Cost-effectiveness acceptability curve

    Conventional subgroup analysis

    An outline of Bayesian cost-effectiveness analysis

  3. Statistical inference in parametric models
  4. Introduction

    Parametric sampling models

    The likelihood function

    Likelihood sets

    The maximum likelihood estimator

    Proving consistency and asymptotic normality

    Reparametrization to a subparameter

    Parametric Bayesian models

    Subjective priors

    Conjugate priors

    Objective priors

    The predictive distribution

    Bayesian model selection

    Intrinsic priors for model selection

    The normal linear model

    Maximum likelihood estimators

    Bayesian estimators

    An outline of variable selection

  5. Statistical decision theory
  6. Introduction

    Elements of a decision problem

    Ordering rewards

    Lotteries

    The Utility function

    Axioms for the existence of the utility function

    Criticisms to the utility function

    Lotteries that depend on a parameter

    The minimax strategy

    The Bayesian strategy

    Comparison

    Optimal decisions in the presence of sampling information

    The frequentist procedure

    The Bayesian procedure

  7. Cost-effectiveness analysis. Optimal treatments
  8. Introduction

    The net benefit of a treatment

    Utility functions of the net benefit

    The utility function U Optimal treatments

    Interpretation of the expected utility

    The utility function U Optimal treatments

    Interpretation of the expected utility

    Penalizing a new treatment

    Parametric classes of probabilistic rewards

    Frequentist predictive distribution of the net bene

    Bayesian predictive distribution of the net benefit

    Statistical models for cost and effectiveness

    The normal-normal model

    The lognormal-normal model

    The lognormal-Bernoulli model

    The bivariate normal model

    The dependent lognormal-Bernoulli model

    A case study

    The cost-effectiveness acceptability curve for the utility

    function U

    The case of completely unknown rewards

    The case of parametric rewards

    The cost-effectiveness acceptability curve for the utility

    function U

    Comments on cost-effectiveness acceptability curve

  9. Cost-effectiveness analysis for heterogenous data
  10. Introduction

    Clustering

    Prior distributions

    Posterior distribution of the cluster models

    Examples

    Bayesian meta-analysis

    The Bayesian meta-model

    The likelihood of the meta-parameter and the

    linking distribution

    Properties of the linking distribution

    Examples

    Contents

    The predictive distribution of (c; e) conditional on a partition

    The unconditional predictive distribution of (c; e)

    The predictive distribution of the net benefit z

    The case of independent c and e

    Optimal treatments

    Examples

  11. Subgroup cost-effectiveness analysis

Introduction

The data and the Bayesian model

The independent normal-normal model

The normal-normal model

The lognormal-normal model

The probit sampling model

Bayesian variable selection

Notation

Posterior model probability

The hierarchical uniform prior for models

Zellner's gpriors for model parameters

Intrinsic priors for model parameters

Bayes factors for normal linear models

Bayes factors for probit models

Bayesian predictive distribution of the net benefit

The normal-normal case

The case where c and e are independent

The lognormal-normal case

Optimal treatments for subgroups

Examples

Improving subgroup definition

저자소개

Elias Moreno (지은이)    정보 더보기
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Francisco Jose Vazquez-polo (지은이)    정보 더보기
펼치기
Miguel Angel Negrin-hernandez (지은이)    정보 더보기
펼치기
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