Statistical Analysis of Cost-Effectiveness Data成本效益数据统计分析 mobi 下载 网盘 caj lrf pdf txt 阿里云

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内容简介:
The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades.
Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author’s own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include:
an overview of statistical methods used in the analysis of cost-effectiveness data.
coverage of Bayesian methodology.
illustrated throughout by worked examples using real data.
suitability for health care professionals with limited statistical knowledge.
discussion of software used for data analysis.
An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
书籍目录:
Preface.
1. Concepts.
1.1 Introduction.
1.2 Cost-effectiveness data and the parameters of interest.
1.3 The cost-effectiveness plane, the ICER and INB.
1.4 Outline.
2. Parameter Estimation for Non-censored Data.
2.1 Introduction.
2.2 Cost.
2.3 Effectiveness.
2.4 Summary.
3. Parameter Estimation for Censored Data.
3.1 Introduction.
3.2 Mean Cost.
3.3 Effectiveness.
3.4 Summary.
4. Cost-effectiveness Analysis.
4.1 Introduction.
4.2 Incremental cost-effectiveness ratio.
4.3 Incremental net benefit.
4.4 The cost-effectiveness acceptability curve.
4.5 Using bootstrap methods.
4.6 A Bayesian incremental net benefit approach.
4.7 Kinked thresholds.
4.8 Summary.
5. Cost-effectiveness Analysis: Examples.
5.1 Introduction.
5.2 The CADET-Hp trial.
5.3 Symptomatic hormone-resistant prostate cancer.
5.4 The Canadian implantable defibrillator study (CIDS).
5.5 The EVALUATE trial.
5.6 Bayesian approach applied to the UK PDS study.
5.7 Summary.
6. Power and Sample Size Determination.
6.1 Introduction.
6.2 Approaches based on the cost-effectiveness plane.
6.3 The classical approach based on net benefit.
6.4 Bayesian take on the classical approach.
6.5 The value of information approach.
6.6 Summary.
7. Covariate Adjustment and Sub-group Analysis.
7.1 Introduction.
7.2 Non-censored data.
7.3 Censored data.
7.4 Summary.
8. Multicenter and Multinational Trials.
8.1 Introduction.
8.2 Background to multinational cost-effectiveness.
8.3 Fixed effect approaches.
8.4 Random effects approaches.
8.5 Summary.
9. Modeling Cost-effectiveness.
9.1 Introduction.
9.2 A general framework for modeling cost-effectiveness results.
9.3 Case study: an economic appraisal of the goal study.
9.4 Summary.
References.
Author Index.
Subject Index.
Series List.
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书籍介绍
The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author's own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include:* an overview of statistical methods used in the analysis of cost-effectiveness data. * coverage of Bayesian methodology.* illustrated throughout by worked examples using real data.* suitability for health care professionals with limited statistical knowledge.* discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
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