• Design
• 34 min
  1. An introduction to randomization for clinical trials 1

  • Prof. William Rosenberger
• 20 min
  2. An introduction to randomization for clinical trials 2

  • Prof. William Rosenberger
• 42 min
  3. Randomisation, blinding and drug supply in interactive voice response trials

  • Mr. Damian McEntegart
• 42 min
  4. Randomization in clinical trials: time for fresh consideration?

  • Dr. Alex Sverdlov
• Analysis
• 32 min
  5. Design and conduct of non-inferiority trials

  • Prof. Valerie Durkalski-Mauldin
• 37 min
  6. Nonparametric covariate adjustment

  • Prof. Michael Akritas
• 34 min
  7. The impact of randomization on the evidence of a clinical trial

  • Prof. Nicole Heussen
• Theory
• 43 min
  8. Historical and ethical issues in trial design

  • Dr. J. Rosser Matthews
• 52 min
  9. Likelihood ratios and the strength of statistical evidence

  • Prof. Jeffrey Blume
• 36 min
  10. Biomarkers and surrogate endpoints in randomized clinical trials

  • Dr. Marc Buyse
• Randomization, Masking and Allocation Concealment
• 22 min
  11. Detection of and adjustment for selection bias in randomized controlled clinical trials

  • Prof. Lieven Nils Kennes
• 46 min
  12. Innovative and effective subject randomization methods

  • Prof. Wenle Zhao
• 12 min
  13. Selection bias in studies with unequal allocation

  • Dr. Olga M. Kuznetsova
• Archived Lectures *These may not cover the latest advances in the field
• 45 min
  14. Design and conduct of equivalence trials

  • Prof. Valerie Durkalski-Mauldin
• 19 min
  15. Dose-finding trials in oncology

  • Prof. Anastasia Ivanova
• 32 min
  16. Allocation concealment, prediction and selection bias

  • Prof. David Torgerson
• 41 min
  17. Pseudo cluster randomization

  • Dr. George Borm
• 26 min
  18. Introduction to flexible, adaptive trial design

  • Dr. Cyrus Mehta
• 30 min
  19. Randomization in clinical trials

  • Prof. William Rosenberger
• 35 min
  20. Novel methods for randomizing

  • Dr. William Grant
• 20 min
  21. Permutation tests

  • Dr. YanYan Zhou
• 59 min
  22. Handling multiplicity due to multiple primary or composite endpoints in clinical trials

  • Dr. Abdul Sankoh
• 32 min
  23. Multiple analyses in clinical trials

  • Prof. Lemuel Moye
• 26 min
  24. Handling of missing data in clinical trials

  • Dr. Linda Yau
• 35 min
  25. A note on the application of post-randomization adjustment

  • Dr. Xun Chen
• 24 min
  26. N-of-1 randomized clinical trials

  • Prof. Patrick Onghena

Printable Handouts

PDF

Navigable Slide Index

1. Introduction
2. Outline
3. Introduction (1)
4. Introduction (2)
5. Introduction (3)
6. Nonparametric ANOVA
7. The hypothesis of interest
8. The hypothesis of no average treatment effect
9. The hypothesis of no simple treatment effect
10. Testing the hypotheses
11. Nonparametric ACNOVA modeling
12. Possible hypotheses (1)
13. Possible hypotheses (2)
14. Possible hypotheses (3)
15. Testing hypothesis of no average treatment effect
16. Testing in the nonparametric ACNOVA model
17. Describing the test statistic
18. The hypothesis corresponds to contrast matrix C
19. Results of simulation study
20. Data sets: the Penn state YWH study (1)
21. Data sets: the Penn state YWH study (2)
22. YWHS: data analysis
23. Data sets: etiology of crime study (1)
24. Data sets: etiology of crime study (2)
25. Etiology of crime: data analysis (1)
26. Etiology of crime: data analysis (2)
27. Etiology of crime :plot of effects (1)
28. Etiology of crime: plot of effects (2)
29. Standardized relative treatment effects
30. References

Topics Covered

• Common parametric and semiparametric approaches for adjusting for covariates, including analysis of variance (ANOVA) and analysis of covariance (ANCOVA)
• The assumptions underlying their validity
• The nonparametric version of the ANOVA model which formulates hypotheses in terms of the cumulative distribution functions as a useful, assumption-free, alternative
• Statistics for testing such hypotheses are extensions of the rank-sum statistic to the ANOVA setting and are implemented with the FANOVA and PROC MIXED procedures in SAS
• An extension of the nonparametric ANOVA methodology to continuous covariates (ANCOVA)
• Simulation results
• Analysis of data examples: the Penn State Young Women's Health Study (YWHS) and the Etiology of Crime Study

Links

Series:

• Design and Analysis of Randomized Clinical Trials

Categories:

• Methods
• Pharmaceutical Sciences

Talk Citation

Publication History

• Published on October 1, 2007
• Reviewed on September 26, 2017

Financial Disclosures

• Prof. Michael Akritas has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.