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Printable Handouts
Navigable Slide Index
- Introduction
- Outline
- Missing data problem - longitudinal trials
- Missing data problem - mechanism
- Industry experience - phase 1
- Neurosciences, phase 2/3 (1)
- Neurosciences, phase 2/3 (2)
- Antivirals (Herpes), phase 3
- Antivirals (HIV), phase 2b/3
- Respiratory, phase 2/3
- Gastrointestinal, phase 2/3
- Metabolic, phase 2/3
- Urology, phase 2/3
- Cardiovascular, phase 3b
- Vaccines, phase 2a
- Diagnostic test (CDRH)
- Medical device (CDRH)
- Issues with LOCF
- Industry guidence - ICH E9
- EMEA, CPMP points to consider
- Sensitivity analyses using multiple imputation
- MI does not create information
- Use of Bayesian process and frequentist approach
- Rubin's MI inference
- Table, fraction of missing data
- Splus software for MI
- Solas 3.0 software for MI
- SAS software for MI
- Notes on MI
- MI example
- MI procedure
- MI analysis
- Concluding remarks
- Obtain all the data you can get
- 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:
Categories:
Talk Citation
Yau, L. (2007, October 1). Handling of missing data in clinical trials [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 13, 2024, from https://doi.org/10.69645/TQUG1861.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Linda Yau has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.