Sample Size and Power Calculation Methods

The statistical approach:

Key questions
• What is the primary outcome measure.
  
• What significance level is difference criterion.
  
• What results are expected in the control group.
  
• How small a treatment difference needs detecting.
  
• With what degree of certainty.

• The expected summary statistic (eg, mean, event rate) of primary endpoint in the control or standard treatment arm of the trial
  
• The smallest treatment effect or benefit that we are trying to detect
  
• The significance level at which we will reject the null hypothesis that there is no difference in the treatment effects
  
• The power with which we want to detect an effect
  
• The design of the study
  
• The expected dropout rate of subjects during the study

• A negative clinical trial is a trial in which the observed differences between the new and standard treatments are not large enough to satisfy a specified significance level (there is a risk of a false positive result or Type I error), so the results are declared to be not statistically significant.
  
• With the benefit of hindsight, analyses of negative clinical trials have shown that the assumptions chosen by investigators often lead them to choose a sample size which is too small to offer a reasonable chance of avoiding a false negative error (a Type II error).

• The sample size is the most important determinant of the statistical power of a study, and a study with inadequate power is unethical unless being conducted as a safety and feasibility study.
  
• However, the calculation of sample size is not an exact science. It is therefore important to make realistic and well-researched assumptions before choosing an appropriate sample size.
  
• This sample size should account for dropouts

If you are in need of help with a sample size and power calculation, please e-mail us at: dmar@dmargroup.com