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- Design
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1. An introduction to randomization for clinical trials 1
- Prof. William Rosenberger
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2. An introduction to randomization for clinical trials 2
- Prof. William Rosenberger
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3. Randomisation, blinding and drug supply in interactive voice response trials
- Mr. Damian McEntegart
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4. Randomization in clinical trials: time for fresh consideration?
- Dr. Alex Sverdlov
- Analysis
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5. Design and conduct of non-inferiority trials
- Prof. Valerie Durkalski-Mauldin
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6. Nonparametric covariate adjustment
- Prof. Michael Akritas
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7. The impact of randomization on the evidence of a clinical trial
- Prof. Nicole Heussen
- Theory
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8. Historical and ethical issues in trial design
- Dr. J. Rosser Matthews
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9. Likelihood ratios and the strength of statistical evidence
- Prof. Jeffrey Blume
- Randomization, Masking and Allocation Concealment
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11. Detection of and adjustment for selection bias in randomized controlled clinical trials
- Prof. Lieven Nils Kennes
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12. Innovative and effective subject randomization methods
- Prof. Wenle Zhao
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13. Selection bias in studies with unequal allocation
- Dr. Olga M. Kuznetsova
- Archived Lectures *These may not cover the latest advances in the field
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14. Design and conduct of equivalence trials
- Prof. Valerie Durkalski-Mauldin
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15. Dose-finding trials in oncology
- Prof. Anastasia Ivanova
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16. Allocation concealment, prediction and selection bias
- Prof. David Torgerson
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17. Pseudo cluster randomization
- Dr. George Borm
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18. Introduction to flexible, adaptive trial design
- Dr. Cyrus Mehta
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19. Randomization in clinical trials
- Prof. William Rosenberger
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20. Novel methods for randomizing
- Dr. William Grant
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21. Permutation tests
- Dr. YanYan Zhou
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23. Multiple analyses in clinical trials
- Prof. Lemuel Moye
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24. Handling of missing data in clinical trials
- Dr. Linda Yau
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26. N-of-1 randomized clinical trials
- Prof. Patrick Onghena
Printable Handouts
Navigable Slide Index
- Introduction
- Outline
- Post-randomization adjustment
- Why post-randomization adjustment?
- Example (1)
- Example (2)
- Regression based method
- A scheme demonstrating the two models (1)
- Concerns on the conventional method (I)
- A scheme demonstrating the two models (2)
- Concerns on the conventional method (II)
- Concerns on the conventional method (III)
- Conventional method (III) - continue
- Alternative methods (I)
- Alternative methods (II)
- Alternative methods (II) - continue
- Alternative methods (III)
- Alternative methods (III) - continue
- Simulation
- Simulation (cont.): conventional regression method
- Simulation (cont.): simple stratification (1)
- FGP/TG values distribution in 4 sub-groups (1)
- Simulation (cont.): simple stratification (2)
- Simulation (cont.): principle stratification (1)
- FGP/TG values distribution in 4 sub-groups (2)
- Simulation (cont.): principle stratification (2)
- Conclusions
- References
Topics Covered
- Adjustment for post-randomization variables: uses in practice to obtain additional information in randomized experiments
- Potential problems of the conventional regression based post-randomization adjustment method: reliability, precision and causality
- Available alternative methods that could provide either more powerful, less biased evaluation or more appropriate assessment for causality
- Examples of the application of the different post-randomization adjustment methods
Links
Series:
Categories:
Talk Citation
Chen, X. (2007, October 1). A note on the application of post-randomization adjustment [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 26, 2024, from https://doi.org/10.69645/HMXS4946.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Xun Chen has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.