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Preventing and Treating Missing Data in Longitudinal Clinical Trials

Book Description

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Table of Contents

  1. Coverpage
  2. Preventing and Treating Missing Data in Longitudinal Clinical Trials
  3. Practical Guides to Biostatistics and Epidemiology
  4. Title page
  5. Copyright page
  6. Contents
  7. List of Figures
  8. List of Tables
  9. Acknowledgments
  10. Preface
  11. Part I: Background and Setting
    1. 1 Why Missing Data Matter
  12. 2 Missing Data Mechanisms
    1. 2.1 Introduction
    2. 2.2 Missing Data Taxonomy
  13. 3 Estimands
    1. 3.1 Introduction
    2. 3.2 Hypotheses
    3. 3.3 Considerations
  14. Part II: Preventing Missing Data
    1. 4 Trial Design Considerations
      1. 4.1 Introduction
      2. 4.2 Design Options to Reduce Missing Data
      3. 4.3 Considerations
  15. 5 Trial Conduct Considerations
    1. 5.1 Introduction
    2. 5.2 Trial Conduct Options to Reduce Missing Data
    3. 5.3 Considerations
  16. Part III: Analytic Considerations
    1. 6 Methods of Estimation
      1. 6.1 Introduction
      2. 6.2 Least Squares
      3. 6.3 Maximum Likelihood
      4. 6.4 Generalized Estimating Equations
      5. 6.5 Considerations
  17. 7 Models and Modeling Considerations
    1. 7.1 Introduction
    2. 7.2 Correlation between Repeated Measurements
    3. 7.3 Time Trends
    4. 7.4 Model Formulation
    5. 7.5 Modeling Philosophies
  18. 8 Methods of Dealing with Missing Data
    1. 8.1 Introduction
    2. 8.2 Complete Case Analysis
    3. 8.3 Simple Forms of Imputation
    4. 8.4 Multiple Imputation
    5. 8.5 Inverse Probability Weighting
    6. 8.6 Modeling Approaches
    7. 8.7 Considerations
  19. Part IV: Analyses and the Analytic Road Map
    1. 9 Analyses of Incomplete Data
      1. 9.1 Introduction
      2. 9.2 Simple Methods for Incomplete Data
      3. 9.3 Likelihood-Based Analyses of Incomplete Data
      4. 9.4 Multiple Imputation-Based Methods
      5. 9.5 Weighted Generalized Estimating Equations
      6. 9.6 Doubly Robust Methods
      7. 9.7 Considerations
  20. 10 MNAR Analyses
    1. 10.1 Introduction
    2. 10.2 Selection Models
    3. 10.3 Shared Parameter Models
    4. 10.4 Pattern-Mixture Models
    5. 10.5 Controlled Imputation Methods
    6. 10.6 Considerations
  21. 11 Choosing Primary Estimands and Analyses
    1. 11.1 Introduction
    2. 11.2 Estimands, Estimators, and Choice of Data
    3. 11.3 Considerations
  22. 12 The Analytic Road Map
    1. 12.1 Introduction
    2. 12.2 The Analytic Road Map
    3. 12.3 Testable Assumptions
    4. 12.4 Assessing Sensitivity to Missing Data Assumptions
    5. 12.5 Considerations
  23. 13 Analyzing Incomplete Categorical Data
    1. 13.1 Introduction
    2. 13.2 Marginal and Conditional Inference
    3. 13.3 Generalized Estimating Equations
    4. 13.4 Random-Effects Models
    5. 13.5 Multiple Imputation
    6. 13.6 Considerations
  24. 14 Example
    1. 14.1 Introduction
    2. 14.2 Data and Setting
    3. 14.3 Objectives and Estimands
    4. 14.4 Analysis Plan
    5. 14.5 Results
    6. 14.6 Considerations
  25. 15 Putting Principles into Practice
    1. 15.1 Introduction
    2. 15.2 Prevention
    3. 15.3 Analysis
    4. 15.4 Software
    5. 15.5 Concluding Thoughts
  26. Bibliography
  27. Index