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Sample Size In Clinical Trials In The Name Of God Sample size in clinical trials.

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Presentation on theme: "Sample Size In Clinical Trials In The Name Of God Sample size in clinical trials."— Presentation transcript:

1 Sample Size In Clinical Trials In The Name Of God Sample size in clinical trials

2 Introduction Sample size in clinical trials

3 Fundamental Point Sample size in clinical trials

4 Fundamental Point Sample size in clinical trials

5 Statistical Concepts Sample size in clinical trials

6 Statistical Concepts Sample size in clinical trials Liying XU (Tel: 22528716) CCTER CUHK 31 st July 2002 Clinical Trial Writing II Sample Size Calculation and Randomization

7 Five Key Questions Regarding the Sample Size What is the main purpose of the trial? What is the principal measure of patients outcome? How will the data be analyzed to detect a treatment difference? (The test statistic: t-test, X 2 or CI.) What type of results does one anticipate with standard treatment? H o and H A, How small a treatment difference is it important to detect and with what degree of certainty? ( ,  and .) How to deal with treatment withdraws and protocol violations.

8 What is  ?  is the minimum difference between groups that is judged to be clinically important – Minimal effect which has clinical relevance in the management of patients –The anticipated effect of the new treatment (larger)

9 The Choice of  and  depend on: the medical and practical consequences of the two kinds of errors prior plausibility of the hypothesis the desired impact of the results

10 The Choice of  and   =0.10 and  =0.2 for preliminary trials that are likely to be replicated.  =0.01 and  =0.05 for the trial that are unlikely replicated.  =  if both test and control treatments are new, about equal in cost, and there are good reasons to consider them both relatively safe.

11 The Choice of  and   >  if there is no established control treatment and test treatment is relatively inexpensive, easy to apply and is not known to have any serious side effects.  <  (the most common approach 0.05 and 0,2 )if the control treatment is already widely used and is known to be reasonably safe and effective, whereas the test treatment is new,costly, and produces serious side effects.

12 Dichotomous Response Variables Sample size in clinical trials

13 Dichotomous Response Variables Sample size in clinical trials

14 Dichotomous Response Variables Sample size in clinical trials

15 Dichotomous Response Variables Sample size in clinical trials

16 Dichotomous Response Variables Sample size in clinical trials

17 Dichotomous Response Variables Sample size in clinical trials

18 Dichotomous Response Variables Sample size in clinical trials

19 Dichotomous Response Variables Sample size in clinical trials

20 Dichotomous Response Variables Sample size in clinical trials

21 Dichotomous Response Variables Sample size in clinical trials

22 Dichotomous Response Variables Sample size in clinical trials

23 Paired Dichotomous Response Sample size in clinical trials

24 Paired Dichotomous Response Sample size in clinical trials

25 Adjusting Sample Size to Compensate for Nonadherence Sample size in clinical trials

26 Adjusting Sample Size to Compensate for Nonadherence Sample size in clinical trials

27 Adjusting Sample Size to Compensate for Nonadherence Sample size in clinical trials

28 Adjusting Sample Size to Compensate for Nonadherence Sample size in clinical trials

29 Two Independent Samples Sample size in clinical trials

30 Two Independent Samples Sample size in clinical trials

31 Two Independent Samples Sample size in clinical trials

32 Paired Data Sample size in clinical trials

33 Paired Data Sample size in clinical trials

34 Paired Data Sample size in clinical trials

35 Sample Size for Repeated Measures Sample size in clinical trials

36 Sample Size for Repeated Measures Sample size in clinical trials

37 Sample Size for Repeated Measures Sample size in clinical trials

38 Sample Size Calculations for “Time to Failure” Sample size in clinical trials

39 Sample Size Calculations for “Time to Failure” Sample size in clinical trials

40 Sample Size Calculations for “Time to Failure” Sample size in clinical trials

41 Sample Size Calculations for “Time to Failure” Sample size in clinical trials

42 Sample Size for Testing “Equivalency” or Noninferiority of Interventions Sample size in clinical trials

43 Sample Size for Testing “Equivalency” or Noninferiority of Interventions Sample size in clinical trials

44 Sample Size for Cluster Randomization Sample size in clinical trials

45 Sample Size for Cluster Randomization Sample size in clinical trials

46 Sample Size for Cluster Randomization Sample size in clinical trials

47 Sample Size for Cluster Randomization Sample size in clinical trials

48 Estimating Sample Size Parameters Sample size in clinical trials

49 Estimating Sample Size Parameters Sample size in clinical trials

50 Multiple Response Variables Sample size in clinical trials

51 Multiple Response Variables Sample size in clinical trials


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