Bayesian Methods in Pharmaceutical Research

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lesaffre, Emmanuel
Otros Autores: Baio, Gianluca, Boulanger, Bruno
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Milton : CRC Press LLC, 2020.
Colección:Chapman and Hall/CRC Biostatistics Ser.
Temas:
Pharmacy > Research > Statistical methods.
Bayesian statistical decision theory.
Théorie de la décision bayésienne.
Bayesian statistical decision theory
Pharmacy > Research > Statistical methods
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Half Title
  • Series Page
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Preface
  • Editors
  • Contributors
  • List of abbreviations
  • Part I: Introduction
  • 1. Bayesian Background
  • 1.1 Introduction
  • 1.2 The frequentist approach to inference
  • 1.3 Bayesian concepts
  • 1.4 More than one parameter
  • 1.5 Choosing the prior distribution
  • 1.6 Determining the posterior distribution numerically
  • 1.7 Hierarchical models and data augmentation
  • 1.8 Model selection and model checking
  • 1.9 Bayesian nonparametric methods
  • 1.10 Bayesian software
  • 1.11 Further reading
  • 2. FDA Regulatory Acceptance of Bayesian Statistics
  • 2.1 Introduction
  • 2.2 Medical devices
  • 2.3 Pharmaceutical products
  • 2.4 Differences between devices and drugs
  • 2.5 Some promising opportunities in pharmaceutical drugs
  • 2.6 The future
  • 2.7 Conclusion
  • 3. Bayesian Tail Probabilities for Decision Making
  • 3.1 Introduction
  • 3.2 Posterior tail probabilities
  • 3.3 Predictive tail probabilities
  • 3.4 Discussion
  • Part II: Clinical development
  • 4. Clinical Development in the Light of Bayesian Statistics
  • 4.1 Introduction
  • 4.2 Introduction to drug development
  • 4.3 Quantitative decision making in drug development
  • 4.4 Bayesian thinking
  • 4.5 Applications of Bayesian methods in drug development
  • 4.6 Conclusion
  • 5. Prior Elicitation
  • 5.1 Introduction
  • 5.2 Methods for prior elicitation
  • 5.3 Examples
  • 5.4 Impact and outlook
  • 6. Use of Historical Data
  • 6.1 Introduction
  • 6.2 Identifying historical or co-data
  • 6.3 An example: Guillain-Barré syndrome in children
  • 6.4 Methods
  • 6.5 Application: Non-inferiority trials
  • 6.6 Discussion
  • 6.7 Code
  • 7. Dose Ranging Studies and Dose Determination
  • 7.1 Introduction
  • 7.2 Dose-response studies
  • 7.3 Dose escalation trials in oncology
  • 7.4 Conclusions
  • 8. Bayesian Adaptive Designs in Drug Development
  • 8.1 Introduction
  • 8.2 Brief history of adaptive designs
  • 8.3 What is an adaptive clinical trial?
  • 8.4 Types of adaptation
  • 8.5 Reasons we might consider adaptive designs
  • 8.6 Example of an adaptive design
  • 8.7 Adaptive enrichment designs
  • 8.8 Some criticisms of adaptive designs
  • 8.9 Summary
  • 9. Bayesian Methods for Longitudinal Data with Missingness
  • 9.1 Introduction
  • 9.2 Common frequentist approaches
  • 9.3 Bayesian approaches
  • 9.4 Ignorable and nonignorable missingness
  • 9.5 Posterior inference
  • 9.6 Model selection
  • 9.7 Model checking and assessment
  • 9.8 Practical example: Growth hormone trial
  • 9.9 Wrap-up and open problems
  • 10. Survival Analysis and Censored Data
  • 10.1 Introduction
  • 10.2 Review of survival analysis
  • 10.3 Software
  • 10.4 Applications
  • 10.5 Reporting
  • 10.6 Other comments
  • 11. Benefit of Bayesian Clustering of Longitudinal Data: Study of Cognitive Decline for Precision Medicine
  • 11.1 Introduction
  • 11.2 Motivating example

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