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Navigable Slide Index

1. Introduction
2. Outline
3. Missing data problem - longitudinal trials
4. Missing data problem - mechanism
5. Industry experience - phase 1
6. Neurosciences, phase 2/3 (1)
7. Neurosciences, phase 2/3 (2)
8. Antivirals (Herpes), phase 3
9. Antivirals (HIV), phase 2b/3
10. Respiratory, phase 2/3
11. Gastrointestinal, phase 2/3
12. Metabolic, phase 2/3
13. Urology, phase 2/3
14. Cardiovascular, phase 3b
15. Vaccines, phase 2a
16. Diagnostic test (CDRH)
17. Medical device (CDRH)
18. Issues with LOCF
19. Industry guidence - ICH E9
20. EMEA, CPMP points to consider
21. Sensitivity analyses using multiple imputation
22. MI does not create information
23. Use of Bayesian process and frequentist approach
24. Rubin's MI inference
25. Table, fraction of missing data
26. Splus software for MI
27. Solas 3.0 software for MI
28. SAS software for MI
29. Notes on MI
30. MI example
31. MI procedure
32. MI analysis
33. Concluding remarks
34. Obtain all the data you can get
35. References

Topics Covered

• The missing data problem
• Missing at random (MAR)
• Industry experience in the handling of missing data
• Last observation carried forward (LOCF)
• Mixed model repeated measures model (MMRM)
• Multiple imputation (MI)
• Sensitivity analysis
• ICH guidelines
• EMEA points to consider document
• Multiple imputation inference
• SAS
• Solas

Links

Series:

• Design and Analysis of Randomized Clinical Trials

Categories:

• Methods
• Pharmaceutical Sciences

Talk Citation

Publication History

• Published on October 1, 2007
• Archived on May 31, 2018

Financial Disclosures

• Dr. Linda Yau has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.