• 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. Three questions
3. Hypothesis testing (1)
4. Hypothesis testing (2)
5. Significance testing (1)
6. Significance testing (2)
7. Bayesian inference (1)
8. Bayesian inference (2)
9. A diagnostic test (1)
10. A diagnostic test (2)
11. The law of likelihood
12. The law says
13. Degrees of strength
14. Three categories of the strength of evidence
15. Diagnostic test, revisited
16. A positive test result and disease presence
17. Irrelevant for data interpretation
18. The diagnostic test
19. Another diagnostic test
20. Question
21. Answer
22. An observed positive result can be misleading
23. The key to the argument
24. Three key concepts (1)
25. Three key concepts (2)
26. Old news
27. The University Group Diabetes Program
28. UGDP data
29. Binomial likelihood
30. Probability of cardiovascular death: placebo (1)
31. Probability of cardiovascular death: placebo (2)
32. Probability of cardiovascular death: tolbutamide (1)
33. Probability of cardiovascular death: placebo (3)
34. Probability of cardiovascular death: tolbutamide (2)
35. Relative risk of cardiovascular death (1)
36. Relative risk of cardiovascular death (2)
37. 'Undesirable' evidence
38. Design considerations
39. Probabilities of misleading and weak evidence (1)
40. Probabilities of misleading and weak evidence (2)
41. Efficiency of sequential designs
42. Simulation
43. Results
44. The universal bound
45. Universal bound holds for sequential designs
46. The bump function
47. Bump equations
48. Probabilities of generating misleading evidence (1)
49. The tepee function
50. Tepee equations
51. Probabilities of generating misleading evidence (2)
52. Probabilities of generating misleading evidence (3)
53. Composite hypothesis (1)
54. Composite hypothesis (2)
55. Relative risk of cardiovascular death (3)
56. So what?
57. Extensions
58. References

Topics Covered

• Using likelihood ratios to measure the strength of statistical evidence in data
• Paradigms for measuring statistical evidence: the three questions
• Likelihood ratios
• The law of likelihood
• The likelihood principle
• Misleading evidence
• Probabilities of observing misleading evidence and their bounds
• Sequential designs in the likelihood paradigm
• Composite hypothesis and extensions
• Example using real data from a well known clinical trial

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 28, 2017

Financial Disclosures

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